Investing in Faros, the engineering bottleneck-breaker
Why we’re backing a $20M Series A for Faros AI, the future of engineering operations, after leading its $16M seed.
Update 6/27/2023: In the wake of layoffs and budget cuts, businesses need tools to optimize their engineering operations more than ever. Meanwhile, teams want to understand whether new AI coding co-pilots actually make them more efficient, or whether they’re just gaining speed at the expense of code quality.
That’s why SignalFire is doubling down with an additional investment in Faros AI as part of a new $20 million Series A raise led by David Hornik at Lobby Capital. Faros’ new Lighthouse AI lets teams use natural language queries to analyze their engineering operations to understand who are their top performers, where bottlenecks occur, and what development tools help. We’re excited to keep supporting Faros with SignalFire’s Beacon AI to help it recruit the best talent after a year of it tripling its customer base and quadrupling annual recurring revenue. If you’re an engineering leader that wants to help your team build software better, faster, and with a smaller headcount, learn more about Faros AI.
Continue reading our post below from 3/2/2022 about why modernizing engineering operations is so important.
Economics has been called the dismal science, and the same label could be applied to software project management. Despite best efforts by very smart people, many if not most software projects end up with missed deadlines, frustrated engineers, disappointed managers and customers, and plenty of politicking after the fact about who should take the blame. My own introduction to this reality came during my very first job out of college as an engineer on Oracle’s database server team about 20 years ago — it was basically taken for granted that schedules would slip and it was part of the duties of a manager to make sure their group wouldn’t be the first to admit they’re causing the whole release to slip and be the fall guys – so you could hide behind someone else’s slippage while trying to get your own team caught up. They don’t teach you that one in college!
Lots of ink has been spilled on reasons for engineering bottlenecks and what could be done. Fred Brooks’ “The Mythical Man Month” is a classic of the genre originally published in 1975, so the problem was recognized a half-century ago. There have been many purported solutions: waterfall to agile, test-driven development, productivity tracking software, and the list goes on. Still, there hasn’t been a silver bullet, and in fact, many of these solutions had the opposite of the intended effect.
Just one example: when IBM started using lines of code as a measure of output, it encouraged bloated code and the opposite of engineering productivity. Maybe another (can’t resist): engineers tend to dislike JIRA because it focuses them on closing the most recent tickets instead of the big picture of shipping product.
The Faros team has experienced these issues first-hand, so they built something better.
Vitaly, Shubha, and Matthew felt the pains of engineering bottlenecks while they were at Salesforce together helping to lead Salesforce’s Einstein team, and in their prior roles at companies like Linkedin. With Faros, their approach to the problem was to recognize that software engineering projects are inherently complex, and there’s no one-size-fits-all approach that can solve the problem of managing them — software engineering is an art AND a science.
What all software engineering projects could benefit from was better visibility into who’s doing what, so that engineers and managers could apply their judgment using the most complete data. Joining data from version control systems, issue trackers, team org charts, CI/CD systems, Faros can give teams a unified map of what’s happening. Additionally, the Faros team had the insight that because no two software development organizations are alike, their platform had to be very flexible and allow for maximum customizability.
By combining a unified data model with the flexibility to customize, Faros puts the most complete data about any software project into the hands of the people running it while leaving value judgments aside. That’s the art Faros leaves to the humans while it takes care of the data part – the science. With Faros, teams ship products faster with fewer resources, and engineers enjoy their jobs more so they stick around longer.
When I first met Vitaly and the team, this vision was just starting to crystallize. Just as Faros helps engineering teams focus on what’s important, SignalFire does the same for our portfolio companies by assisting them with recruiting, growth, and PR. For example, our resident data science PhD Olivia Angiuli helped Faros build customer lead lists to speed up their go-to-market motion.
Fast forward two years, and we are thrilled to see Faros announce its $16 million seed fundraise. And more important than the capital are the terrific customers like Box, Coursera, Salesforce, and GoFundMe who are using Faros to ship their software projects on time and on budget. If you’re a software engineer or manager who’s interested in checking them out, please go to https://faros.ai/ or just drop me a line. Break those bottlenecks and get back to building!
How EvenUp’s AI gets justice for personal injury victims
AI deepens data moats. With the world’s newfound ability to synthesize enormous volumes of information to extract and apply what matters, power is shifting to whomever builds the biggest and best data sets.
SignalFire is itself an applied data business at its core, disrupting the archaic, service-oriented industry of venture capital with our Beacon AI for investment sourcing and portfolio recruiting. So it’s probably no surprise we are ardent students and fans of data-driven businesses. We are inspired by companies like CoreLogic or Verisk—two of the most profitable multibillion-dollar businesses around that own data monopolies within real estate and insurance. Now EvenUp is claiming its position as the first AI legal assistant.
EvenUp’s AI SaaS tool for personal injury law firms analyzes medical records and similar cases to suggest fair compensation and automatically generates legal documents to help plaintiffs get the compensation they deserve. SignalFire invested at the seed, led their Series A in 2021, and now we’re excited to be backing EvenUp’s $50.5M Series B, led by Bessemer Venture Partners.
Like real estate and insurance, litigation finance is a massive, opaque $100B industry that profits from information asymmetry—between big insurers with enormous amounts of data on claims payouts, and plaintiffs’ lawyers who only have data from the cases they’ve handled. EvenUp is building a proprietary database of legal data for free from law firm customers through its workflow SaaS (unlike CoreLogic for real estate analytics, which has to pay for self-reported surveys). They’re also ultimately bringing transparency to an industry notoriously vulnerable to scams, while its data helps qualify victims for financing as they await a payout. And like Verisk for financial risk analytics, EvenUp helps lawyers pool data to help them predict the outcomes of cases.
“The advantages of possessing a substantial dataset cannot be overstated. Access to a larger volume of data allows us to train more capable models, but it also means we can capitalize on higher signal and lower noise data generated by these models for downstream tasks. In essence, a more extensive dataset is a catalyst for innovation” EvenUp CEO Rami Karabibar tells us. And while they built credibility to gain access to law firms’ data, EvenUp used whatever it could find. “We had to rely on weaponizing public data to start, which took us many months of engineering and data science work to make valuable, but it was better than shipping an inferior product quickly.”
And the company is a perfect example of a vertical SaaS business supercharged by a new generation of foundation models. EvenUp ingests and analyzes about a million pages of medical documents every week. They’ve built their own deep learning annotation models to pull information about injuries, procedures, and medical coding from these records. But copying and pasting this unformatted data and text from a medical record into a legal document is not what a judge or insurance adjuster wants to see.
That’s where ChatGPT comes in. EvenUp can take a number of bullet points from medical records that are “rough around the edges” language, and turn them into concise paragraphs that make a legal case. This is extremely compelling, because this is where the bulk of a personal injury attorney’s time goes: taking these data points and succinctly making a case in prose. Before large language models, the best alternative would have been to build templates to create these summaries, which don’t always work perfectly.
It’s hard to understate the massive time savings EvenUp generates. In some cases, it can take days to generate a demand package—the demand for compensation plus all supporting documentation such as medical bills and case details. For medical malpractice cases or class action lawsuits, there can be 30,000 pages of medical records or more. Producing a fully vetted demand package immediately for such a case would be game-changing for personal injury lawyers who support an extremely high volume of cases.
This is a specialized use case for ChatGPT, and only possible because EvenUp brings their own dataset of legal cases. This dataset gets richer with each new lawyer they bring on as a customer, and each new case they handle, giving EvenUp a powerful data network effect. And the company needs a lot of data, as they need to understand the prospective value of every type of potential injury for every potential insurer.
Rami and Saam are among the most ambitious and thoughtful founders we’ve met. They are extremely deep in the problem space, sharp yet genuinely kind, humble, and fun people to be around. And they’ve been incredible at attracting other amazing talent to the company, including their first engineering hire, Matyas Tamas, who’s a legend as Quora’s first data scientist—sourced through SignalFire’s proprietary Beacon system! The founders have been power users of our system since the very beginning as they’ve scaled the company quickly in less than two years to more than 100 employees after we invested at the seed and led the series A.
EvenUp is already well on its way as the clear market leader, but we at SignalFire think we’re just in the early innings of an incredible social mission to level the playing field for victims of car accidents, abuse, and more.
Security, meet CX: Why we invested in Strivacity
These days, consumers are more likely to enter their favorite businesses through a digital front door than a physical one. This creates a unique challenge for companies: how can they ensure a seamless and easy online experience for their customers while also keeping their customers’ personal information secure? It’s a delicate balancing act between providing convenience and safety.
On one hand, the CMO wants to make the registration and sign-in process as easy as possible, removing friction and allowing customers to create accounts, sign in, and use their services in novel ways. On the other hand, the CISO’s responsibility is to ensure there are no data breaches or hacked accounts. This tension creates an extremely difficult business problem in today’s digital-first world. Companies have two options:
- Tighten the system too much and you see new customer registrations, usage, and conversion rates plummet.
- One leading national hotel chain implemented one-size-fits-all multi-factor authentication (MFA), increasing friction for their users: revenue fell 11%.
- Relax the constraints and your brand risks being a front-page headline and losing customer confidence.
- Account takeover (ATO) has become an increasingly prevalent issue in recent years. Account takeover fraud losses reached $3 billion in 2022, according to Javelin Research—and that doesn’t include reputational damage.
Enter Strivacity—a new kind of customer identity and access management (CIAM) software provider, designed around a cloud-based “configuration-as-code” offering. Because of its architecture, business-critical changes can be made without needing expensive and time-consuming engineering resources. This allows the CMO or Head of Digital to experiment and iterate quickly on customer experience (CX) workflows, while the CISO can rest assured that the underlying authentication system is secure and automatically kept current with associated enterprise infrastructure. Due to this flexibility, Strivacity can ensure its CIAM platform will meet the needs of the enterprise C-suite and revenue-function owners. This makes it unlike most existing solutions, which are tailored almost exclusively to the technical teams inside a large organization.
That’s why SignalFire is excited to lead Strivacity’s latest $20M investment round.
One size doesn’t fit all
Strivacity understands that workforce identity and customer identity solutions have very different security and user experience needs. Instead of trying to cram these solutions together, Strivacity focuses solely on the needs of customer identity management and has been deliberate in its approach to building a seamless CIAM platform. From a single console, an administrator is able to control and orchestrate registration, sign-in and authentication, identity verification, consent management (for data privacy), and ongoing fraud prevention. Other providers have stitched these capabilities together via M&A alongside an alphabet soup of modules for workforce identity management (PAM, IGA, IDTR, etc.), resulting in disjointed architectures and significant engineering and consulting maintenance costs. In fact, during our due diligence, one enterprise customer estimated that Strivacity provides a 30% annual total cost of ownership (TCO) reduction versus their legacy vendor.
“We started Strivacity because we saw a familiar and frustrating story replaying itself over and
over at Fortune 1000 companies. Workforce-centric identity solution providers were force-fitting their products to serve customer use cases. The results were invariably monthslong rollouts that ended with organizations settling for poor customer experiences and writing big checks for after-market services,” said Keith Graham, Strivacity’s co-founder and CEO.
An all-star team for identity security
Strivacity’s founders, Keith Graham (CEO) and Stephen Cox (CTO), have been working together on enterprise cybersecurity solutions for more than ten years, most recently leading teams at SecureAuth and Mandiant. In fact, Kevin Mandia (founder and CEO of Mandiant) was so impressed with the product vision and early customer traction, he invested and joined their board of directors.
Jack Huffard (co-founder and former COO of Tenable) invested alongside SignalFire, and joined Strivacity as Executive Chairman. We have been working with Jack as part of our XIR program for about a year to find an innovative cybersecurity company that was re-imagining “identity” solutions for the enterprise—and to our good fortune, we found Strivacity.
“With Strivacity, improving security with customers doesn’t require increasing friction for users. They’re pioneering a new approach to customer identity and access management (CIAM) that’s synchronized with marketing to let enterprises optimize both in tandem. Between SignalFire’s recruiting and growth help, my experience scaling Tenable into a public company, and the Strivacity founders’ vision for the future of CIAM, we can vastly improve the security and experience customers have with the brands they trust.”
—Jack Huffard, Chairman of Strivacity, Co-Founder of Tenable (NASDAQ:TENB), SignalFire XIR
As they were looking for their next investor, Keith and Stephen wanted a partner who would actively help them scale the business. Keith shared:
We are thrilled to be partnering with this team and co-investing with Todd Weber (former CTO of Optiv), partner at TenEleven Ventures. With this unparalleled group of cybersecurity experts around the table, and an innovative approach to orchestration, we believe Strivacity is the future of CIAM.
The market is voting…
We’re not alone in our opinion of this product and team—industry analysts and early customers are raving about them as well. Strivacity is the only startup recognized as a Leader in The Forrester Wave™: Customer Identity and Access Management, Q2 2022. And on the customer side, leading enterprises across gaming, online education, financial services, and consumer software rely on Strivacity to manage their customer registration, sign-in, and privacy workflows.
Strivacity is faster to deploy, easier to support, and more comprehensive than any other CIAM solution in the market. The balance of simple and customizable CX with strong cybersecurity is a delicate one. With Strivacity, that balancing act becomes cheaper, faster, and easier to achieve. Finally: something that both the business side and the IT side of an enterprise can agree on.
*SignalFire may engage Affiliate Advisors, Retained Advisors, and other consultants as listed above to provide their expertise on a formal or ad hoc basis. They are not employed by SignalFire and do not provide investment advisory services to clients on behalf of SignalFire. For more information on their specific roles, please contact us. Portfolio Company Endorsements: Certain portfolio company founders or Affiliate Advisors listed above may or may not be current investors in a SF fund in which they receive a fee reduction. Such fee reductions were not provided in exchange for or an incentive for their feedback, nor contingent upon the individual’s approval for SignalFire’s continued use. Please refer to our website for additional disclosures.
The Patient Engagement Revolution: Why we led Wellth’s $20M Series B
Healthcare costs Americans a staggering $4.1 trillion dollars each year. But what actually drives all that cost? One glaring, seemingly avoidable factor is patient behavior. Six in ten adults in the U.S. have a chronic disease— the conditions that lead to 86% of our healthcare costs. Individual behaviors—attending doctor’s appointments, taking medications as prescribed, and “knowing your numbers” are crucial in managing these chronic conditions. In fact, $300–500 billion each year is wasted just as a result of prescription medication non-adherence and mismanagement, according to the National Institutes of Health.
That’s why we’re leading a $20M Series B round into Wellth, the leader in leveraging behavioral economics to drive adherence to prescribed care and treatment plans. You can read more about the news from Wellth and Fierce Healthcare.
As mentioned above, six in ten Americans suffer from a chronic health issue—including both authors of this piece. That’s more than 200 million of us dealing with ongoing treatment programs. To reduce the waste from non-adherence, Wellth is pioneering better ways to incentivize this group to remain steadfast in their treatment plans, focusing on a massive needle mover: motivation. Specifically, engaging and motivating the population that is most at risk of going astray from healthy decision-making—the 25% of Medicare beneficiaries that incur 96% of the costs(!).
Behavior: The true unlock
Forty percent of health outcomes can be linked directly to personal decisions—not genetics, not quality of care, and not social determinants like income, according to the Kaiser Family Foundation. We all have friends or family who know they need to get to the gym to be healthier but can never quite stick to it. There’s a big difference between knowing what we need to do to take care of our health and actually doing it. Especially for senior citizens and lower-income Americans—people who may not have the time, energy or motivation to keep up with daily health choices—leading patients to disengage from their care plans.
Disengaged behavior takes many forms: skipping appointments, forgetting medication, not checking key health signs frequently, etc. These may sound like minor slip-ups, but they can often cause extremely harmful (and expensive) effects down the line. Consider:
- Heart attack: Patients who don’t take their heart medications after a heart attack are 2x more likely to have a second heart attack in the next three months.
- Kidney disease: Patients with end-stage renal disease (ESRD) who miss one dialysis appointment are 3x as likely to end up in the hospital (and have 50% higher mortality).
- Diabetes: Patients with diabetes who don’t check their glucometers or miss oral insulin prescriptions can be unaware of their blood sugar being either far too high or far too low. There were more than two million diabetes-related emergency room visits annually in the U.S. in 2021.
How Wellth helps
Wellth uses behavioral economics to drive better outcomes, primarily through a monthly rewards system. Patients use the Wellth app to document daily healthy behaviors (like taking their medication as directed)—and depending on the activity, a fraction is deducted from their reward if it’s not completed.
Wellth’s programs are delivered by leveraging key behavioral psychology principles such as:
- Loss aversion: A $10 loss feels worse to us than how good a $10 gain feels
- The intent-behavior gap: What we plan to do doesn’t translate to what we will do
- The endowment effect: We value things more when we own them
Wellth partners with some of the nation’s largest health insurance companies (e.g., United Healthcare, Centene) to motivate their most vulnerable members. Wellth reaches out to these people, gets them to download the app, and motivates daily action with their treatment plan.
The rewards members receive are subsidized by those health insurers, and depending on the program, they are triggered by different user inputs—it may be snapping a picture of pills in your hand, showing a glucometer reading, or confirming presence at appointments. In each case, it’s as easy as texting a photo. That’s why Wellth has engagement rates that are completely unheard of in healthcare. 91% of Wellth’s users use the app every day. That’s 3x the engagement rate of TikTok’s user base.
In short, Wellth uses modern technology to get people to actually make the decisions that they know they ought to make, benefitting both their physical health, and the health of the U.S. healthcare system as a whole. Wellth’s co-founders, CEO Matt Loper and CTO Alec Zopf, have kept their mission of a healthier America front-and-center as they built this company together, leveraging expertise from prior careers in healthcare advisory and data engineering.
The proof that Wellth works
Great, so people log in and use the app. But that sounds like we’re spending more money, doesn’t it? Where’s the proof that people engaging with the app actually saves money downstream, by avoiding ER visits and the like?
Having served more than 30,000 patients, the outcomes are nothing short of a revelation:
- Missed appointments: Decreased 15% (keeping the system moving efficiently)
- Emergency room visits: Decreased 29% (ER visits are incredibly costly)
- Days spent in the hospital: Decreased 42% (hospitalizations are even more costly)
- Annual savings per patient: Over $2,500
- Total savings to the U.S. healthcare system: $50+ million to date
Across the estimated 30 million polychronic and disengaged individuals in the U.S., Wellth could eventually reduce the cost of the U.S. health system by over $75 billion.
Why Wellth chose SignalFire
Before investing in Wellth, SignalFire spoke to more than 50 companies in the patient engagement space. We determined that patient behavior change around medication non-adherence was the most important problem to solve. When we saw the engagement rate, the increased adherence, and the savings to health plans Wellth was generating, we knew we’d found a winner.
Every investment is a two-way street. So once we decided to work with Wellth, they had to decide to work with us. When asked why they did, Wellth’s CEO Matt Loper told us:
“Every venture fund I’ve ever met has promised to add value beyond capital—but SignalFire is the first I’ve known to exceed all expectations. They uniquely understand the challenges founders face and have purpose-built their team to help them overcome those challenges. Every team member is an expert in their field that goes above and beyond to help their portfolio companies. Chris Farmer and Chris Scoggins have seen firsthand how companies define industries and scale. Tawni and Heather help us think through how to best grow our team. YY and Tony immediately became a key extension of our executive team. And of course, there’s SignalFire’s XIR Frank Williams, who is a force of nature and would be a first-ballot inductee into the Healthcare Hall of Fame. Working with Frank and the whole SignalFire team has already proved to be a dream come true.” —Matt Loper, CEO of Wellth
Matt is referring to the unique Executive-in-Residence (XIR) program that SignalFire designed for situations just like this one: pairing A) startups serving a clear market need and with the potential to be generation-defining companies, with B) deeply experienced industry leaders in their field who have founded and scaled massively influential companies.
In this case, to help find a company working on a solution to the patient motivation problem, SignalFire partnered with XIR Frank Williams, former CEO of the Advisory Board Company (acquired by Optum for $2.5B) and founder/CEO of Evolent Health (NYSE:EVH, $3B+ market cap).
Williams, who is joining as the chairman of Wellth’s board of directors, shared, “I haven’t seen a venture firm that has made such a comprehensive investment in supporting entrepreneurs in scaling their businesses successfully.” He added:
Health outcomes are driven by behaviors, and Wellth is fundamentally evolving the way we think about healthcare behavior change. We are incredibly excited to be a part of the journey alongside Matt, Alec, and the entire L.A.-based Wellth team, as well as their new chairman Frank Williams. There are so many systemic issues in today’s healthcare system that it can feel impossible to change, but Wellth is showing us that with technology and an innovative approach to patient motivation, we can make a real difference.
And they’re hiring! If you want to help make a change in the way we take care of ourselves in this country, reach out!
*SignalFire may engage Affiliate Advisors, Retained Advisors, and other consultants as listed above to provide their expertise on a formal or ad hoc basis. They are not employed by SignalFire and do not provide investment advisory services to clients on behalf of SignalFire. For more information on their specific roles, please contact us. Portfolio Company Endorsements: Certain portfolio company founders or Affiliate Advisors listed above may or may not be current investors in a SF fund in which they receive a fee reduction. Such fee reductions were not provided in exchange for or an incentive for their feedback, nor contingent upon the individual’s approval for SignalFire’s continued use. Please refer to our website for additional disclosures.
Funding Fixie’s LLMOps to unlock AI for enterprise
We’re missing the true value of large language models by keeping them stuck in a chat box. LLMs will be a staple of tomorrow’s machine learning startup opportunities, but only if their impact can be felt where we already work today.
Not long after ChatGPT became a thing, people discovered LLMs could do more than just predict the next word for a sequence of text. Given instructions or when asked to solve a problem, the language model would iterate step-by-step to solve that problem. People started to build on top of LLMs. While the models began with text autocomplete, they’re now used to break down problems into subtasks and execute them one-by-one.
Yet what the language models lack today is the ability to connect with external systems. The genie is out of the bottle. The models are out there. The question is how to use them in the context of an enterprise while not violating standards for privacy and safety.
Large model APIs help engineers get started faster. They take them for some part of the journey but don’t carry them the last mile to the destination. What corporations want to accomplish is usually quite specific, and building a custom solution often makes the most sense. As Ines Montani, the CEO of Explosion, a SignalFire portfolio company, says: “Eventually, the large model will be one part of the toolbox, and ‘surprisingly good’ won’t be good enough; you’ll want something ‘better’.” Her co-founder, Matthew Honnibal, adds that “ultimately users care about how high the ceiling is, not how the high floor is.”
Building powerful apps on top of large language models with Fixie
Currently, there is a flurry of LLM startups, many of which are using LLM models without any fine-tuning: they just stuff as much info into the prompt and allow the model to take it and use it to refine itself. While this is the quickest way to make use of this space, we believe it won’t scale very well. Differentiation comes from the data moat, the extended capabilities of the product, and the tastes and elbow grease of the humans building these products. For enterprise, we believe that customers want flexibility when using any ML model and any framework. They want the experience to be provider-agnostic, hosted wherever they are, and without vendor lock-in. This is why we invested in Ivy to unify all ML tooling, spaCy/Explosion for providing an Open Source NLP toolbox and annotation system, and most recently we invested in Fixie as the pioneers of LLM adoption for enterprises.
Fixie provides extensions for language models to access external systems, allowing people to ask questions, get responses, and take action. With Fixie, customers can build natural language agents that connect to their data, talk to APIs, and solve complex problems. It’s designed from the ground up with enterprise customers in mind, offering them maximum flexibility and robustness that is necessary to serve enterprise use cases. If you are a company who wants to add LLMs to your application, reach out to learn more or play with the product https://www.fixie.ai/.
The team has a strong background building large-scale systems and AI-powered products for billions of users. Matt Welsh, the CEO, was a professor of computer science at Harvard (one of his students was Mark Zuckerberg). After nearly killing Facebook, Matt spent time at Google, Xnor.ai, Apple, and OctoML. Zach Koch, the CPO, is a former product director at Shopify, and was previously a product lead at Google on the Chrome and Android teams. CTO Justin Uberti was the head of the Stadia, Duo, and Hangouts Video teams at Google, and was one of the inventors of WebRTC. Hessam Bagherinezhad is the chief AI officer, and he was an AI/ML leader at Apple and the first employee at Xnor.ai.
SignalFire loves working with experienced AI teams because we build AI ourselves. For the past decade we’ve had a half-dozen engineers working on our Beacon AI data platform, which helps us source investments and assist our portfolio companies with hiring. With all the new AI companies popping up, recruiting top talent in the space can be a challenge. If you’re building an AI company that wants to use AI to find AI engineers, come talk to us at SignalFire or email me at [email protected]. I’m a machine learning engineer, too, who’s willing do anything to help founders succeed.
Why Signalfire funded CodaMetrix to fix medical billing
Healthcare is under threat of an enormous labor shortage, caused in large part by an aging workforce. Across the industry—physicians, nurses, administrators—many workers are expected to retire in the next decade, with not enough young people entering the profession to replace them. According to the American Journal of Nursing, 4 million nurses are expected to retire by 2030. Add to that an increasing rate of burnout due to COVID.
One particularly interesting, relatively unknown healthcare profession that’s also been affected is the medical coder. It’s a niche role—there are approximately 140,000 people in the U.S. and an additional 150,000 globally, in the trade. A coder’s job is to take doctors’ notes and come up with a combination of one or more Current Procedural Terminology (CPT) codes, and one or more ICD-10 codes (International Classification of Diseases, 10th Revision) that are used to express the type of care that was delivered to meet payers’ reimbursement guidelines and requirements. There are literally billions of combinations.
Depending on the type of care provided, this could quickly become a very complex task. For example, if you go to your primary care doctor for a routine appointment, it’s usually a highly structured visit where several standard checks are performed, maybe a blood test is ordered, and you’re good to go. But let’s think about something like an inpatient visit: you’re staying in a hospital for a week because you just had surgery; you have multiple, varied interactions with your surgeon, the anesthesiologist, other specialists, and multiple nurses; all over the course of those seven days. The work to record this activity accurately is enormous. The “doctors’ notes” from your weeklong stay can become the length of a term paper. Coders then have to extract the key information to generate dozens and dozens of billing codes, or worse yet in some cases the physicians have to do that themselves, which takes them away from patient care.
Across the U.S., health systems spend a collective total of $9 billion annually on medical coding. And despite the large spend, the current state of coding is challenging—it’s highly manual, and so errors happen— in fact the recent Becker’s Hospital CFO Report shows 42% of denials are due to coding inaccuracies. Currently, miscoding can lead to costly back-and-forth communications between Providers and Payers, and undercoding can lead to Providers being underpaid for necessary services they delivered to patients.
Medical coding should be largely automated—enter “Applied AI”
Given SignalFire’s strength in data and analytics, AI, and specifically machine learning (ML) and natural language processing (NLP), we were particularly excited about how automation can play an outsized role in the medical coding space for four key reasons:
- Coders are quickly aging out of the workforce. The average medical coder is approximately 50 years old, and fewer young people have been entering the field. Providers must find a way to scale their coding capacity, while making their existing employees more productive.
- Coders are humans and humans make mistakes. We’ve all heard hospitals complain about Payers denying some portion of their claims. On the other hand, Payers complain that hospitals try to squeeze more reimbursement from them by billing for more services than were performed—a concept called “upcoding.” In reality, both sides are right, but very rarely do claims get denied because of fraud (intentional upcoding). Instead, the problem is usually human error. In the weeklong inpatient visit example above, it wouldn’t be unusual for a coder to make mistakes and input incorrect codes. Also, the list of codes changes and new codes are released annually or quarterly. Coders need training to keep up with the latest and they have to keep up with their CEU (Continuing Education Units) to maintain their certifications.
- ML and NLP technology advancements have now made coding automation feasible with high accuracy. Natural language processing technology was not mature enough until recently to tackle challenges for automated coding. Many of these NLP systems required hand-annotated training data, which had poorer quality results. It wasn’t until 2013 that there was a big breakthrough in deep-learning–based methods (starting with a language model called word2vec), which created a step function improvement in accuracy across all NLP tasks. For example, Google Translate was first publicly released in 2006 but was able to improve accuracy by 60% when they switched to a deep learning model in 2016. Furthermore, NLP applied to the medical field saw exponential improvement in 2020 as researchers released deep learning language models focused specifically on medical notes (called BioBERT).
- More compliant adoption of Electronic Health Record systems (“EHRs”) and highly scalable and affordable cloud computing. US healthcare Providers and Payers alike have made significant investments in electronification of both clinical and billing data. Now, this large corpus of data can be used by fairly reliable, secure, and affordable cloud and AI infrastructure to both clean the data to develop the ground truth data needed to train Machine Learning (ML) models that not only take advantage of more advanced NLP, but also add the pattern recognition and statistical analysis dimension to produce even better results.
Between 2014 and 2018 many startups began working to apply the more mature NLP systems to medical coding. Fast forward to 2023 and we now finally see a small cohort of autonomous medical coding companies that have achieved product-market fit but are still in the early stages of crossing the chasm to achieve adoption widely. It’s not a surprise that companies have taken several years to get to this point. It requires an enormous amount of time to obtain a large training data set, train and backtest the models until they work, convince the typical hyper-conservative-unwilling-to-try-any-new-technology healthcare organization to use their solution, and finally integrate with all of their existing workflow solutions—all before any revenue is generated. But we believe the market is finally ready for these solutions, because ML and NLP technology advancements have enabled these solutions to actually deliver the results they claim.
When we built a market map of all the medical coding automation companies that have product-market fit (defined as having at least a handful of customers and a minimum of several million dollars of revenue) there were only a few that made the list. At SignalFire, we believe the companies that will win over time are those with products built on a true machine learning approach and with teams that have experience working inside US-based health systems. CodaMetrix was the only company with both.
ML is the right platform approach to this technology problem. We think it’s best positioned to extend across specialities over time. The alternative to using an ML model is a simpler rules-based NLP system—the concept that if a doctor wrote X, Y and Z keywords and phrases, then output would be specific billing (CPT and ICD) codes. However, the pure rules-based NLP systems do not scale well because changes in documentation style and every subsequent speciality product developed will require a new set of rules to be programmed. When a system relies on a large set of rules, that’s when it becomes “brittle” and will require lots of caring and feeding to function properly. Currently, companies in this space begin with one or two specialities (for instance, CodaMetrix started with radiology and pathology, and has now expanded to offer surgery, inpatient coding, etc.). But as the autonomous coding platforms need to handle a larger number of specialties and subspecialties, the ML approach, vs. NLP-centric, promises to have the chops to handle the complexities.
However, ML platforms are useless without an abundance of accurate training data. Because CodaMetrix was incubated and launched inside Mass General Brigham (MGB)—one of the largest and most innovative health systems in the country—it has had unparalleled access to large volumes of training data on any specialty. The company’s cutting edge deep learning models can quickly “learn” the terminology and coding guidelines (or “patterns”) of a new speciality, enabling a rapid product development cycle. This allows CodaMetrix to get its new, tested products into the hands of customers faster than the competition.
One important, yet subtle, feature of its platform is “code transparency.” Because the company started from day one as a product built for a health system (MGB), the tech team also creatively designed the architecture to solve for a key challenge in the industry—showing the reasoning behind its AI decisions. Most machine learning models are black boxes, but CodaMetrix has a built-in audit trail feature in their product so one can see what information the system specifically used to reach its conclusion. This is incredibly rare, yet valuable, in machine learning solutions and a must-have in healthcare, where Providers are frequently audited by Payers to determine if they are coding appropriately.
CodaMetrix’s ability to build products tailored for health systems is driven by an experienced team who deeply understand the ecosystem. The executive team, which has decades of experience working inside and with health systems, is led by CEO Hamid Tabatabaie who was previously an Entrepreneur-in-Residence at MGB, and formerly the CEO and Founder of LifeIMAGE.
The early results are impressive. Today, CodaMetrix is a multi-specialty platform that classifies codes across radiology, pathology, surgery, gastroenterology, and inpatient professional coding with customers across 10 health systems and major academic universities, representing 111 hospitals in 40 states, including Mass General Brigham, University of Colorado Medicine, Yale Medicine, and Henry Ford Health Systems. Customers using CodaMetrix have seen significant increase in cost savings and cash acceleration—from 70% reduction in manual labor, 59% reduction in denials, and improved cash collection by as many as 47 days.
Why CodaMetrix and MGB chose SignalFire
SignalFire is honored to be leading CodaMetrix’s $55M Series A alongside Frist Cressey Ventures, Martin Ventures, Yale Medicine, CU Healthcare Innovation Fund, and Mass General Brigham physician organizations. SignalFire’s proprietary AI data platform Beacon—which tracks 495 million employees and 80 million companies—stood out to CodaMetrix’s CEO Hamid Tabatabaie as a demonstration of our depth in AI and data as one of the key reason why he chose us to lead the Series A, amongst many others.
“SignalFire’s mantra of adding value beyond the check was evident from the onset and further pronounced with every step along the process. The impeccable combination of Yuanling Yuan’’s in-depth industry research, Tom Peterson’s continuous involvement, SignalFire’s in-house AI and data expertise, Chris Scoggins’ infectious drive for scale, Chris Farmer’s refreshing healthcare thesis, and the brilliant team of experts in talent, operations, and go-to-market strategists are clear reasons for us to have selected them as the lead investor.’ – Hamid Tabatabaie, CodaMetrix CEO
We are also thrilled to have the support of Mass General Brigham in selecting SignalFire as a long-term partner for CodaMetrix.
“Mass General Brigham is delighted to have SignalFire lead the Series A and attract a strong syndicate. SignalFire brings to CodaMetrix deep AI/ML and go-to-market commercialization expertise that will ensure CodaMetrix continues to build on those capabilities developed at Mass General Brigham and lead the market in autonomous medical coding to help drive down healthcare administrative costs and reduce physician burnout. In the short time that SignalFire has been involved with CodaMetrix, they have already demonstrated how their focus on data and GTM expertise will add value.” — Gaye Bok, Partner of AI and Digital Innovation Fund, Mass General Brigham
The team at CodaMetrix was excited about SignalFire’s unique XIR program, which pairs deeply experienced tech industry leaders from the firm’s Advisor Network with high-potential portfolio companies to help accelerate their growth. Tom Peterson, SignalFire’s XIR who will be very actively involved at the CodaMetrix board level and advising on day-to-day operations, boasts 20+ years of deep healthcare experience as the co-founder and former COO of Evolent Health (NYSE:EVH) and former executive director of the Advisory Board Company (acquired by United Health and Vista Equity Partners for $2.6B).
“Given the strength of the leadership team and the connection to MGB, I was really impressed with the depth of CodaMetrix’s understanding of health systems and how that was combined with best-in-class technology to develop industry leading coding automation products. CodaMetrix is the only coding automation company out there that is built for the health system ecosystem by people who deeply understand it.” — Tom Peterson, SignalFire XIR and co-founder and former COO of Evolent Health (NYSE:EVH)
We are incredibly excited to see how the medical coding automation space evolves over the next decade. This solution is coming just in time, as hiring managers in the industry are likely to face a steep challenge replacing a soon-to-be retiring workforce. With investments like CodaMetrix, we see a future where healthcare Providers can save on labor costs, ensure proper billing for services rendered and achieve faster pay reimbursement thanks to a much lower rate of claim denials. All of these will help our overburdened health systems to remain financially solvent as they try to keep up with the rapidly increasing needs of U.S. patients.
*SignalFire may engage Affiliate Advisors, Retained Advisors, and other consultants as listed above to provide their expertise on a formal or ad hoc basis. They are not employed by SignalFire and do not provide investment advisory services to clients on behalf of SignalFire. For more information on their specific roles, please contact us. Portfolio Company Endorsements: Certain portfolio company founders listed above have not received any compensation for this feedback and did not invest in a SignalFire fund. Please refer to our website for additional disclosures.
Funding ‘Grow Therapy’ to get mental health covered by insurance
Depression and anxiety rates are up 300% and demand for mental health services has grown 200% in just a few years since the start of the pandemic. Yet 55% of all US counties don’t have a licensed behavioral therapist. Mental health is clearly one of the most pressing issues for our healthcare system.
Grow Therapy is tackling this crisis in two critical ways: Making therapy a more attractive profession, and getting therapy covered by insurance.
Grow equips therapists with all the tools they need to launch their own practice: a virtual receptionist for scheduling, billing systems, telehealth infra, health records, and marketing help through Grow’s own site and featured placement on channel partner platforms. The ability to be one’s own boss, set one’s own hours, keep more of the revenue, and decide what conditions to focus on helps the therapy profession attract and retain better talent.
Then, to make therapy affordable for everyone, Grow strikes partnerships with top payors and programs to get its therapists covered by insurance, including Medicare and Medicaid. That’s how it’s quickly grown to over 3,000 providers who it helps serve over 10,000 new patients each month, and how it increased revenue 13X in the last year. After leading its Series A, we’re excited to back Grow Therapy’s $45M Series B led by our friends at TCV (plus $30M in debt funding).
Grow occupies arguably the most strategic position at the heart of the massive structural demand-supply imbalance for mental health services, which unfortunately will get worse before it gets better. It’s building the most robust practice enablement offering covering everything a therapist needs to get their practice off the ground. They are best positioned in the long run because they are building a much stickier and deeper relationship with therapists who run their entire practice through Grow.
Moreover, they’re unlocking net new supply through a vertically integrated approach targeting therapists who have yet to start their own practice. The vertical integration also means Grow has a much greater ability to fundamentally improve the patient experience (for example allowing the company to collect more patient data, and transition to more acute care in a way that the other thinner aggregators can’t do). All of this in turn makes them the best mental health practice enablement platform for payors and the broader healthcare ecosystem.
It’s a hugely disruptive value proposition that grows the market 10X to the vast majority of people who can’t afford to pay out of pocket for a hugely important service. I’ve had my own family life turned on its head during the pandemic from a relative’s mental health episode. I was born in Detroit and raised by an immigrant family from rural Taiwan, and had we still been in that kind of financial situation or job inflexibility, I have no idea what we would have done. Grow’s specific approach cuts to the core of that problem, as they are the only ones who have an economic model that allows them to accept Medicare/Medicaid (which the new practices that Grow is helping launch are happy to take, unlike existing practices).
The Grow Therapy team is special. We’ve backed first-time and repeat founders including the creator/CEO of YouTube, the ex-CEO of Jawbone, the ex-President of Zynga, the ex-head of GoogleX Robotics, and the ex-VP of Engineering of Amazon. I can confidently say Jake and the Grow team are among the most thoughtful and fastest learning in our portfolio. They are execution machines, but are also genuinely kind and fun to be around.
The company is growing at an incredible pace, among the fastest and most efficient we’ve seen at their stage. Their competitive fundraise during a summer when the market for such growth rounds was effectively frozen is an indication of how much of an outlier they are. Grow Therapy is the kind of business that can endure and thrive in any market environment. Now it has the funding to address the most underserved health epidemic of our generation.
How OneSignal pivoted to power notifications for 1 in 7 apps
After leading its Series A and B, SignalFire backs OneSignal’s new $50M Series C
There’s a grand tradition amongst ambitious gaming startups. When their game proves too heady, before its time, or simply too weird, they pivot to selling the infrastructure they built along the way. Fates Forever became Discord. Glitch became Slack. So too did Go Ninja become OneSignal…and developers around the world better off because of it.
George Deglin and his team had grown frustrated with the weak push notification infrastructure available to his previous company Hiptic games. Without notifications, a once loyal but absentminded player could forget about Go Ninja and churn out. The existing solutions weren’t enterprise-focused, self-serve, performant, or affordable. So they decided to roll their own.
Pretty soon not just gaming companies were demanding access, and the company went all in on the pivot to selling push notification infrastructure. Within a short time, OneSignal wracked up 300,000 registered users by offering a product-led service with a generous free tier where users could sign up and be sending notifications within minutes without having to talk to anyone – exactly what they were once looking for.
The secret sauce was OneSignal’s ability to run their infrastructure very efficiently, reminding me of my days at Google. OneSignal’s technical team used dedicated hardware (no cloud services!) and efficient systems programming languages (Rust) to process billions of push notifications at an extremely low cost.
After we at SignalFire made our initial investment in 2017, we doubled down in 2019. Our cultures aligned – both teams are full of data nerds eager to help their fellow engineers. While they built out push infra, we helped them build up their team with our own homegrown recruiting technology Beacon. It helped them find not just the strongest PMs and engineers, but the ones that were most likely to leave their job for a new challenge.
OneSignal’s torrid growth continued, and today it has 1.7M registered developers and marketers. It processes over 10B notifications per day and has rolled out an omnichannel product, making it a one-stop shop for any company that needs to communicate with its users via mobile push, web push, email, SMS, or in-app messaging. OneSignal processes more notifications than all of its competitors combined, and 1 out of every 7 new mobile apps uses OneSignal.
To power its continued growth and continue its ascent to becoming the default way that developers communicate with customers the company today announced a $50M Series C led by Jamie McGurk at BAM Elevate. Rather than building a few games, George and the team are empowering an entire generation of developers of all stripes. And they seem to be having even more fun doing it.
The need for real-time data monitoring: Leading $34M for Dig Security
If someone breaks into your house but your alarm doesn’t go off until eight hours later, that’s not really “security”. Yet this is how most data cybersecurity systems work today. Most security platforms can’t detect an attacker early enough in the kill chain to actually stop them and prevent further damage. Today, a motivated attacker can breach cloud data in less than three minutes!
This whole problem has only gotten worse as the shift from on-prem to the perimeter-less cloud causes data sprawl. Now businesses don’t even know where all their data is, and you can’t use agents or hardware to intercept all traffic. You need to monitor out-of-band and through APIs, safeguard microservices. Simply put, the old network-centric approaches don’t apply.
What we need is real-time security — where the alarm goes off the moment someone breaks in so the cops show up and catch them in the act before they can escape with your stuff.
That’s how Dig Security works so it can detect incursions in under a minute. Dig indexes and monitors all your cloud data stores and structures. After identifying and minimizing any static risks, Dig helps companies establish policies for approved data access. That lets businesses rapidly discover anomalous use and respond to shut down access and keep attackers from stealing their sensitive user data, payment information, or intellectual property. Finally, Dig provides audit records so businesses can prove to regulators that they’re keeping sensitive data safe.
The need for this modern approach to data is why SignalFire is leading a $34 million Series A for Dig Security. We believe they’re the future of data detection and response for the perimeter-less era. In a post-firewall world, Dig can give tech companies, financial institutions, governments, and others the peace of mind that their data is safe. You can read more about Dig in TechCrunch.
In the on-prem era, data security was essentially a highly secure vault. Anyone who wanted access to sensitive data would need to authenticate themselves and customers were able to put in place firewalls and alarm systems since they owned the real estate. But with the move to the public cloud, customers now face a slew of new problems. These include their data being dispersed across many different environments, not having full control or ownership over the cloud they run on, and needing a real-time alarm system that could cover their fragmented data.
Unfortunately, most cloud security vendors today only focus on helping customers locate their sensitive data in the cloud and build weak checkpoints around it. They don’t have visibility into what’s done with the data, so they never detect anomalous use. Dig changes this by not only finding and protecting the data stores but also offering an actual real-time alerting system so customers get notified of anything suspicious.
Building this fundamental overhaul of how we approach security requires deep experience at high stakes. Luckily, CEO Dan Benjamin was previously running security product strategy for the world’s biggest enterprise cloud — Microsoft Azure. Before that, he was the CTO of Google Cloud for Startups after serving with the Israeli Defense Force’s elite 8200 cybersecurity division. He built the way the world’s top businesses and militaries approach cloud security, and now he’s bringing that depth of protection to every company through Dig. Meanwhile, our Beacon Talent recruiting engine ranks Dig’s engineering team in the 95th percentile of all startups we index.Unfortunately, customers can’t wait and hope for the big enterprise clouds to handle data security properly. In fact, Dan got the idea for Dig after Google Cloud launched an API that let users export their whole production data asset as a CSV…which promptly let a hacker steal everything from one of Google Cloud’s top customers. Dan realized the need for a dedicated data security solution outside of the cloud platforms themselves that are too big to care about the problems their updates cause.
At SignalFire, we love providing our portfolio companies with help they can measure. That’s why founders give us an NPS of 92 when few funds even track that metric. Our go-to-market experts led by ex-Stripe CMO Jim Stoneham are helping Dig reach the customer leads identified by our in-house data science team. Our recruiting leaders are working with Dan to use our Beacon Talent engine to hire the best engineers. And SignalFire’s in-house PR expert Josh Constine, a former editor at TechCrunch, advised them on making a big splash with today’s funding announcement.
“This is an amazing team of second-time entrepreneurs with the scars from paying their dues in the security industry” says SignalFire advisor and Exabeam security founder Nir Polak. “They not only have the right idea that data is the crown jewel that enterprises are trying to protect. They also know how to execute.” Now Dig’s focus is making it easier and easier to integrate while expanding into Data Loss Prevention to protect data in motion, at rest, and at its endpoints.
Every technological shift comes with tradeoffs. All the convenience, collaboration, and flexibility of the cloud are accompanied by increased risks from a fragmented attack surface that firewalls can’t protect. Dig will let organizations safely seize the cloud’s benefits by providing the real-time vigilance they need to catch crooks red-handed.
Investing in Twingate, a VPN your team will actually love
For me, the word “VPN” conjures up frustration: sluggish network connectivity with videos buffering and downloads slowing to a crawl, plus general clunkiness where certain applications stop working altogether. Most of us have had experience with VPNs at work — they’ve unfortunately been a standard way to access corporate networks for decades at this point.
The problem stems from how traditional VPNs are architected: you connect to a VPN server which then forwards your network traffic to its final destination and then forwards the response traffic that comes back to you. It becomes the single choke point for all your data and an extra leg that has to be traveled for every request. That’s a lot of overhead, especially if the VPN server is far from you or becomes overloaded.
The price you pay in speed may have made sense in the past when all IT resources were on-premise and the VPN could govern secure access to them. In today’s world, the rise of SaaS apps that run in the cloud has rendered that model obsolete. Why should your Zoom calls or Gmail attachment downloads slow to a crawl over a VPN for no security benefit? Additionally, VPN servers have themselves become a prime target for hackers. Capture the VPN server and the hacker gets the keys to the entire kingdom.
This is where Twingate comes in. We first got to know Tony Huie, the co-founder & CEO, when he joined SignalFire from Dropbox as an investing partner. When Tony got the itch to go back to operating and founded Twingate, we were thrilled to back him at seed. The vision he laid out for a modern rethinking of the VPN (and access controls more broadly) resonated and the technology behind the product was battle-tested.
By intelligently routing your traffic directly based on its destination, Twingate eliminates the VPN server middleman. It maps your networks with no need for on-prem or cloud infrastructure changes, then analyzes every network request to verify the user, device, and context. Twingate then uses resource-level split tunneling, NAT traversal, and private proxies to ensure there are no user performance or latency problems.
Twingate’s ease of use for both end-users and admins has been a focus for the team which has deep Dropbox roots and an appreciation for the power of great UX. Equipped with SignalFire’s Beacon Talent hiring engine, recruiting team, and data scientists, Tony has led Twingate to tremendous growth this past year and a half. It also won over 50 awards from G2 including easiest to use, best support, and best ROI!
We’re pleased to participate in the latest $42 million Series B round of financing which the company announced today in Forbes. The team is on a roll and they have an exciting roadmap to build atop their initial VPN replacement use case, helping companies of all sizes migrate to a new security model based on Zero Trust.
If you want to replace your VPN with something your team will love, you can get set up with Twingate in just minutes.
Manage Open Source Sprawl with Plural
Why OSS deployment is broken, and SignalFire is funding Plural to fix it
Consuming OSS today is truly painful. Outdated OSS is the norm in the industry. As per OSSRA “85% of the codebases contained open source dependencies that were more than four years out-of-date. Unlike abandoned projects, these outdated open source components have active developer communities that publish updates and security patches. But these patches are not being applied by their downstream commercial consumers.”
Plural is changing the narrative by empowering developers of OSS and the DevOps teams consuming it. Plural provides a single, seamless experience to manage all your open source applications. No more toggling between 30 different vendors and dozens of different management tools that hardly integrate with each other. Plural’s mission is to deliver a great developer experience for consuming OSS software, while rewarding the community that wrote the code.
Today we are pleased to announce SignalFire’s investment in Plural, leading their $6M seed round. We are thrilled to be of service to such an awesome team, providing help from our recruiting engine Beacon Talent, advisor network, and in-house experts on data science, fundraising, PR, and growth.
The managed service approach to open source
Developers have two options: either use a managed service where possible or build and maintain the end-to-end stack themselves. We’ve come to realize there are some underappreciated flaws to the managed service approach to open source. The most well-known is that by taking full control of the application, incentives become misaligned on the part of the cloud provider: they generate undue pricing power which locks developer communities out of the monetization of their products.
But more deeply, the managed service model makes you entirely dependent on the cloud provider’s priorities to use your applications as you’d like. Any feature or configuration is funneled through their bandwidth-constrained team to implement, and if they aren’t willing, you’re out of luck. This often creates a graduation problem, where you eventually outscale the service. This constraint also limits the ability of teams to adopt a lot of the long tail of open source, which will not be fully supported by the likes of AWS, GCP, etc since it won’t meet their hurdle rate for investment.
Further, by creating a service boundary between hundreds of disparate systems in your stack, you end up moving the problem of application maintenance to integration maintenance. Your DevOps team won’t necessarily be manually babying an elasticsearch cluster, but they will be babying the myriad of systems that cluster talks to and all the proprietary tools needed to interact with them.
Automating Away Operational Knowledge Bottlenecks
Today’s codebases are large and only getting more complex. As per SourceGraph, in their Big Code report, over 6 out of 10 developers have noticed an increase in the variety of tools, languages, repositories, devices, and architectures.
The best-performing companies start with a top-tier infrastructure team that has the operational knowledge to run their systems. As the company scales and the complexity increases, even those with amazing infra teams are running into operational knowledge bottlenecks. When they can’t find people to operationalize the OSS software, they oftentimes never adopt the software they want in the first place. The operational knowledge that was trapped in the heads of a few people is no longer saving the day and instead causes an embarrassing mess. Plural converts this tribal knowledge into software and with that software, companies can now consume open source infrastructure without so much pain and cost.
As Plural cofounder and CEO Sam Weaver said in VentureBeat, “As open source software proliferated and fragmented, it became needlessly complex for enterprises to deploy. Miss one of the two hundred integration steps, and your system breaks. That led developers to rely on overpriced managed services as a way to get going fast, without the overhead of setup. Plural fixes this by aggregating the top open source software, and then abstracting away all the deployment and operations complexity.”
Developers do more of what they want instead of writing and maintaining code about code
As companies gain more traction, the infrastructure has to scale to support the volume and serve customers where they are – regardless of geography. But this fortunate trajectory puts stress on the engineering team which is forced to focus on code about code instead of building the actual product that got them excited in the first place. They start compromising on cost, autonomy, and flexibility by using a managed service, but soon realize how limiting it is and how they still have to write and maintain glue code. Once they have to go international, they might realize the managed service vendor does not have a footprint abroad, and that they need more bells and whistles as they get to scale and sophistication.
With Plural, all you need to do is issue two commands and you’re up and running. You have all the observability and logging baked in, integrated with the security stack etc. It’s all k8s, you can deploy it in your cloud or on-prem, and it feels like the cloud. The developers are deriving a ton of value from consuming well-integrated technology while being cheaper and more customizable than a managed service. It feels like a fully managed service, Plural delivers updates for the application, you can always get the latest and greatest without having any effort on your side. Plural untangles your open source into a clean two-step experience.
OSS vendors get rewarded
The relationship between Plural and OSS vendors is designed to be complementary. Plural is not a hosting provider and does not take full ownership of the application, the customer does. Most established OSS vendors often monetize around 10% of their usage. The vast majority of users are managing themselves under the radar. Plural can help the vendors to monetize the long-tail of users or at least capture leads better. And it can do it much quicker, providing all the plumbing in a scalable way by bringing the market to the vendors. Newer OSS vendors can also choose to use Plural to start to monetize early, by utilizing the observability, support, and multi-cloud installation from Plural.
The Plural team, led by Sam and Michael, has extensive experience deploying and managing OSS via k8s and running large-scale production systems, as well as contributing to open source software. We are stoked to put our whole team and data science platform behind them, and support them in building a great platform for DevOps teams and the OSS community, as well as a diverse company culture and a sustainable business. We’re happy to welcome Plural to the SignalFire portfolio!
Instead of hiring, skill up your employees with Modal
Why SignalFire led a $6.8M seed for Modal‘s data scientist training platform from the ex-CEO of Udemy
The gating factor to software transforming every type of business continues to be talent. You can’t build, grow, analyze, or sell without the right humans. Unfortunately, they’re all quitting. Over 4 million workers left their jobs every month during the second half of 2021. This “Great Resignation” is leaving companies vastly understaffed, spurring a domino effect. If your teammate leaves, their work doesn’t disappear, it gets dumped on you, which makes you want to leave…
Perhaps the biggest talent bottleneck today exists around data scientists. Product, marketing, operations, and sales teams are constantly asking “Can our data scientist look at this?” only to hear back, “maybe next quarter…if ever.” Decision-making velocity is slowed down by a backlog of these requests to a centralized team of data analysts and scientists.
Enabling teams to be self-sufficient in answering their own data questions would be a massive unlock for data-savvy organizations, and one of the reasons we invested in Unsupervised to let business teams perform their own data analysis. But most companies still need dedicated data talent, not just technology. And for all but the best-branded tech giants with tons of cash to burn, recruiting them is remarkably difficult. It’s tough to compete with Google salaries
Training > Recruiting
Luckily, we’re at an inflection point for learning systems. Beyond traditional universities and on-the-job training, we’ve seen an explosion of online courses and free YouTube tutorials on YouTube. It’s never been easier to pick up a new hobby, soft skill, or craft. Yet humans remain mediocre at self-directed learning. With no schedules, tests, grades, classmates, or one-on-one help, it’s no wonder online course completion rates average around 15% for apps like Coursera, and only 20% to 30% for classes offered by Harvard and Stanford. And even those that make it through all the lecture videos won’t necessarily have learned a skill well enough to do it as their job.
If there was a more reliable way to teach skills, companies could shift from unsuccessfully trying to hire expert talent like data scientists to skilling up their tens of thousands of existing technical and IT employees. These staffers want the challenge, career development, and compensation of learning more hardcore skillsets. Training them and giving them a raise is still far cheaper than recruiting. Plus, companies would end up with proven talent that knows where the technical bodies are buried.
Modal turns your team into data scientists
This is exactly why Modal is building a better approach to corporate training for Fortune 500 companies. Modal replaces those boring and ineffective training videos with deep cohort-based courses. Students collaborate directly with coaches, work on group projects with co-workers and colleagues from other companies, practice using real-world scenarios, and complete technical assessments that measure their mastery.
Modal delivers 15X more engagement than traditional corporate training and helped 87% of beta customers’ students meet their learning objectives. Meanwhile, it helps companies save money on recruiting, improves employee retention through career development, and ensures roles get filled so businesses can keep building. Today, Modal’s skill assessments help employers measure progress on skill-building and route talent into the right roles. But soon, its data on employee skills and career pathways could enable Modal to assess an organization’s open technical jobs, and find the right employees who could fill them.
Modal was founded by Dennis Yang and Darren Shimkus, the former CEO and the former enterprise President of $2.2 billion education giant Udemy. Together they scaled Udemy’s enterprise business to 9 figures in revenue, and precisely understand what employers need from education. Dennis and Darren pioneered the last generation of online learning, recognized the opportunities to improve it, and are now the perfect people to launch the definitive corporate edtech business.
SignalFire invests more than money
As a deeply technical firm ourselves, we are hugely bullish on democratizing the power of data science across the Fortune 500 by enabling these companies to train their own. That’s why we’re leading Modal’s $6.8M seed round, and equipping them with our own Beacon recruiting technology and other value-adds. They join our portfolio of startups fighting The Great Resignation including Praisidio’s employee attrition early warning system, Included’s diversity and inclusion data platform, and Candidate Labs’ AI-assisted recruiting firm. We at SignalFire couldn’t be more excited to partner with the Modal team to help more employees skill up for the job of their dreams.
Investing in Superdao, the all-in-one DAO platform
Aligned incentives are the fastest way to build and grow. When everyone gains, everyone contributes. Yet traditional corporate structures divorce private companies from their largest potential source of assistance: their users. Beyond paying for their products and perhaps enjoying the fuzzy benefits of network effects or early adopter prestige, customers gain little if the companies they love succeed. Unless they apply to work for them full-time, or wait around for them to go public, customers are largely locked out of helping build or earning returns.
Web3 erases the line between customers and teammates. With DAOs, or decentralized autonomous organizations, outsiders can quickly become insiders. Tokenomics allow them to be commensurately rewarded for contributing even small denominations of capital or labor. Your cult following can become your collaborators. In an age of COVID isolation, remote work alienation, and secularization, the chance to participate and find a sense of belonging is tantalizing.
That’s why we’ve seen DAOs form to build startups, launch social clubs, invest at scale, create media, and work on philanthropic projects. In the future we expect DAOs to take on many additional forms that we can’t even fathom yet. That includes TAOs, or transformed autonomous organizations, where traditional companies create DAO-like subsidiaries to participate in Web3 alongside their customers or even just pay employees or contractors in crypto. By aligning incentizes with a large crowd of community members, DAOs hold enormous power to direct labor, capital, attention, and impact. They’re the new organizational structure that allows groups to transact with cryptocurrency and provide token rewards to their allies.
But to launch a DAO, fund a treasury, organize a workforce, and vote on governance proposals, it requires piecing together a fragmented set of infrastructure tools built for hardcore blockchain engineers. You have to know what tools exist, which ones work best, and how to stitch them together alongside Web2 components (such as Discord and Google Sheets) that were not meant for this use case, all while hiring hard to find smart contract engineers to handle much of the governance pieces. And that’s before you even get to the sociological challenges of managing a large group of people!
This all creates unnecessary barriers blocking participation in a rapidly emerging economy. To empower a more diverse set of builders, we need tools that abstract away the complexity so communities and organizations can focus on what they uniquely add to the world.
When Shopify combined intuitive commerce tools with attractive storefronts, a new generation of merchants emerged. Making something people want to buy was hard enough without having to build or jigsaw together your own software stack. But what if you want to start a movement?
Superdao is building the Shopify of Web3 – an all-in-one, no-code DAO creation and management suite for organizing people to make an impact.
Superdao lets anyone launch a DAO in a few clicks without having to vet and master a mess of siloed point solutions. Meanwhile, it helps sophisticated DAO operators scale their organizations by letting them seamlessly stitch together Superdao’s native features with their favorite existing blockchain infrastructure.
With Superdao you can:
- Legally incorporate while launching your DAO on the blockchain
- Crowdfund a secure treasury for transactions and paying contributors
- Build a member directory with varying roles and permissions
- Communicate through internal feeds for organizing tasks
- Vote on governance proposals using vetted templates and smart contracts
- Monitor activity and tokenomics through your DAO’s dashboard
- Decentralize ownership with tokens, NFTs, and equity options
- Integrate with leading third-party infrastructure apps
- Recruit talent and capital through Superdao’s discovery marketplace
- And a lot more soon – this is just the alpha launch
You can sign up here to get early access!
While Superdao is designed to be dead simple for users, it’s a compound startup that requires building a suite of pioneering tools in parallel. Web3 moves ridiculously fast, so Superdao needs a leader with super-human ability to ship product.
We found that in Yury Lifshits. After earning a PhD in Computer Science from Caltech and teaching cryptography at a leading Russian university in the mid-2000s, he launched one of the country’s first co-working spaces. We met Yury while he spent the past few years building OpenLand, a full-fledged alternative to another essential Web3 tool: Discord. Yury builds and deploys products with insane speed and clarity. He’s an astounding organizational mind that’s able to recruit and apply talent to get things done quick. Yury has already assembled a world-class team creating the building blocks that will power the future of DAOs. We’d never encountered an early-stage founder with such exacting plans for who he wanted to hire, how to structure the teams, what he wanted to build, and how he planned to go-to-market.
Yury’s precision and horsepower convinced he could shoulder the complexity of making DAOs simple. That’s why SignalFire is leading a $10.5 million seed round for Superdao. Yury predicts we could see 1 million DAOs formed by the end of the year, and Superdao will provide their picks-and-shovels. The deal continues SignalFire’s specialization in funding world-changing infrastructure companies like Alchemy for blockchain and NFT infrastructure, Tapcart for mobile ecommerce, Planetscale for databases, and Bubble for no-code app development.
Superdao’s goal is to be the leading B2B infrastructure provider for DAOs. They’ll allow everyone from crypto-native communities to relative novices to operate DAOs as Hollywood, Wall Street, traditional tech, and other sectors get involved. Superdao will bridge the gap between users and builders, letting anyone tap into the power of tokenomics to create a unified community where customers become co-owners and co-conspirators.
DAOs will take a variety of forms including classic blockchain protocols and DeFi projects, groups of strangers looking to do a single transaction (ie purchase an expensive item, plot of land, etc), Web3 companies with their own tokens, Web2 companies looking to pay individuals (employees, contractors, freelancers, etc) in some form of cryptocurrency, and social experiments that will surprise and excite the world. We can’t predict exactly what they’ll do or how they’ll work, but with a team as agile as Superdao, we know they’ll have the tools they need.
Want to build your own DAO? Wish yours ran more smoothly? Sign up for early access to Superdao.
Care-Now-Pay-Later: Why SignalFire is leading $15M for PayZen
79 million Americans have medical debt or bill problems. Sadly, the inability to pay or fear of debt has led 1 in 3 Americans to delay or decline essential medical care.
This has to change. And that’s why we’re leading a $15 million Series A for PayZen, the care-now-pay-later company.
PayZen helps any patient get on a zero-interest, zero-fee custom payment plan so they can receive the care they need immediately without going into debt. How? PayZen’s AI analyzes thousands of data points about their financial situation to ensure they’re on a payback schedule they can afford, instead of the industry-standard one-size-fits-all plan. That’s why 87% of patients offered PayZen enroll, and it increases their payment adherence by 40% within one month. You can learn more about how PayZen works here.
Meanwhile, PayZen helps hospitals increase collections by 52%. Typically, hospitals collect just 15 cents of every dollar they charge while sending people to collection services that destroy their credit score. By integrating PayZen, care providers give their patients a more understanding and affordable approach. They share a portion of the extra payments they receive with PayZen so patients aren’t charged extra fees.
Building a true win-win-win solution like this takes a combination of healthcare veterans, fintech experts, and skilled engineers. That’s the team PayZen assembled. CEO Itzik Cohen, COO Tobias Mezger, and CTO Ariel Rosenthal had previously worked together and seen how legacy approaches had failed providers and patients. They’ve joined forces with Kevin Roberts, the CFO of 3 million patient healthcare group Geisinger, and industry legend Lawrence Leisure who co-founded ADVI Health, Healthspottr, and healthcare investment fund Chicago Pacific Partners.
Together, we see their potential to address the healthcare affordability crisis plaguing our country. Many of our LPs at SignalFire are large health systems, and their leaders told us how badly they need a solution like PayZen. We’re honored to get to support the company with our Beacon Talent recruiting technology, in-house AI experts, and network introductions team.
PayZen is the kind of startup that makes us proud to be investors. When technology is applied with empathy, it can solve some of society’s greatest challenges. We can’t think of a larger or more pressing one than ensuring everyone can afford the healthcare they need.
Funding Praisidio to fight The Great Resignation
In Q2 2021 alone, 11.5 million Americans quit their jobs, the vast majority being mid-career tech and healthcare workers, leaving their employers scrambling to fill rolls and desperate to stop the exodus. This year will be remembered as the beginning of the “Great Resignation”.
Employee attrition was already a $1 trillion annual problem in the US and the pandemic has only made the problem larger. Historically, managers saw their employees in the office on a daily basis and could get a read on how their team was feeling. In a remote work environment, it’s harder than ever to keep talent engaged and happy. Businesses need an employee attrition early warning system. Enterprises only have exit interviews which are backward-looking to help understand why employees leave the company, but in an age where there is more 1st and 3rd party data than ever before, the time seems right to leverage these valuable insights to help solve the problem of employee attrition.
A Personal Mission
When we met Ken Klein and Vahed Qazvinian it was clear from the first meeting that to them, this problem was personal. After watching a key team member’s departure cause seven of his colleagues to resign in quick succession and cause their project to be canceled, Vahed, a PhD and former Google Search Rank Engineer, decided to leave himself. As a former public company CEO, Ken has felt the cultural and financial pain of attrition, despite many attempts at remediation through HRBP meetings, skip-level 1:1s, office hours, surveys, and more. After discussing their shared experiences, this unique and powerful duo decided to partner up on a mission to improve the employee experience and arm HR leaders with the data they need to retain their most important assets. And thus, Praisidio was born.
Combining Data with Human Intelligence
Praisidio uses AI to analyze business and communications metadata in a privacy-centric manner. The company provides an Enterprise Talent Risk Management solution called Procaire to help managers visualize and act on information that is affecting employee satisfaction and retention. Procaire has already helped over 10,000 employees within enterprise customers across the technology, life sciences, and healthcare sectors. Customers are saving $50 on talent attrition for every dollar spent on Praisidio.
At SignalFire, we believe in the power of combining humans and data and when we saw what Vahed and Ken were building at Praisidio, we knew we wanted to be on the journey with them. SignalFire is thrilled to be leading Praisidio’s $4M Seed round and helping them achieve their goal of making employees feel engaged and appreciated while empowering managers and HR teams with the insights they need to be data-driven in their decisions and initiatives around employee retention. To learn more, check out Praisidio.com where you can hear how happy customers are already seeing success with Procaire.
Adobe acquires Frame.io for $1.275B: Future of video collaboration
You absolutely cannot miss this deadline. The director, client, and special effects artists all have urgent feedback that has to make it into the next cut. You’re collecting reshoots from the videographers, juggling versions from your editing team, reviewing marked-up clips from the colorist, and making sure nothing leaks before it airs.
But to make this video truly brilliant, you have to stay in flow. There’s no time to manually move files between storage services, dig suggestions out of email, or trek back to the office to access raw footage. Luckily, you don’t have to. Like Disney, HBO, and Netflix, your team uses Frame.io to collaborate on video production so you can do it all in one app from anywhere.
Building software like this for professional creatives requires the mind of an engineer and the heart of an artist. We found both in Emery Wells when we met in a Palo Alto coffee shop 6 years ago. He beamed with empathy for video producers because he’d spent over a decade doing it himself. That inspired us to invest in Frame.io’s seed round and every raise since.
Hit skip to replay the video above
Frame’s product releases have become favorites amongst our team because each is paired with its own red carpet-worthy launch video. The company puts its own software to use editing these gorgeous trailers, demonstrating their deep respect for the craft.
Now he and his team at Frame.io have the opportunity to help the world’s biggest creative software clients stay in sync so they can create gorgeous video content. Today, Adobe announced it will acquire Frame.io, where Emery will continue to lead his team towards building the future of video production in the cloud.
“Anyone that’s paying attention knows the future of work is real-time, centralized in the cloud, and collaborative. Video has been an industry that has been slower to adopt the cloud but we’re standing at the precipice of the next major step-function change in the way video gets created” Emery says. “It will be as significant as the shift from analog to digital.” He’s ready to lead that shift at Adobe.
Emery started as a production assistant before becoming a compositor, motion graphics artist, executive producer, and eventually the founder of his own post-production agency Katabatic Digital where he created shorts for Saturday Night Live. That meant when he launched Frame.io with Katabatic’s Chief Scientist John Traver, they were building for themselves. The startup saw an opportunity to arm independent producers with even better software than the biggest studios.
They knew video can’t be treated like most static files that move through Box or Dropbox. It’s a rare art form that takes an enormous team to create, and constantly evolves before release. It requires powerful specialty software like Adobe Premiere Pro and AfterEffects to compose, yet there was no ubiquitous product for collaborating around its completion.
Frame.io has built a powerful product to fill that gap, but also a unique company culture where both creatives and engineers can thrive. Creatives often crave flexibility and autonomy, doing things their own way. Engineers are more accustomed to reliable processes. Our operating partner Tawni Cranz had navigated a similar challenge as the Chief Talent Officer of Netflix, and offered ideas on how the company could remain free-spirited while staying on schedule.
“SignalFire was one of our first investors and has been incredible partners throughout our journey” Emery graciously tells us. “I’ll never forget when it came time to hiring our first recruiter. This was a new and unfamiliar role to me at the time. SignalFire flew their Head of Talent Mike Mangini to New York City to personally interview our candidates and make a recommendation. I think it was a great example of their grit and hands-on approach to working with their portfolio companies.”
The Frame.io team was put to the test this past year as cloud collaboration became essential. With offices closed and employees working remotely, studios couldn’t rely on huge editing bays and on-prem software to securely stay in sync. Frame.io picked up the slack as the industry shifted towards the cloud that Emery and his team had been preparing for years.
Adobe saw this inevitable transformation coming too. Reimagining its Creative Suite for the cloud massively expanded accessibility, both in the sense of letting artists work from anywhere as well as creating a monthly pricing structure that made it easier to try. Now Frame.io’s integrations with Adobe’s Creative will get even tighter so creatives can concentrate on what they do best.
Video has become the default communication medium for the next generation. It’s persuasive and emotionally resonant, effortlessly immersing the audience rather than feeling like a chore. With larger phone screens and faster mobile networks, the market for video compounds each day. It’s journalists relaying scenes from the front lines, creators becoming heads of full-fledged studios, brands showing their products in action, and blockbuster filmmakers evoking our wildest dreams. Video tells the story, and the storytellers live on Frame.io. Congrats to Emery, John, and the whole team on reaching the ultimate scale with Adobe.
Funding “Flymachine” to make URL concerts as good as IRL
Music lovers deserve more than sitting by themselves watching single-camera streams from an artist’s basement. The livestreamed music experience should evoke the same excitement of arriving with friends or serendipitously running into them, and the kinetic immersion of a great concert venue’s sound system and stage lights — all while letting you see the best artists anywhere from the comfort of your home.
Musicians tried their best this past year with the limited tools they had, but concert streams felt more like Zoom calls than culture. Bands like Sofi Tukker who streamed every single day did society a great service, but too often, the level of added work didn’t match the compensation.
To give fans a worthy concert-going experience while supporting the music industry, you need to help:
- Artists earn money streaming shows without piling more work upon their already busy schedules
- Venues bring fans the intimate close-ups and entrancing light shows they’d get in-person while paying their staffs
- Fans feel the camaraderie of attending concerts with friends, even when they’re apart
Flymachine’s concert streaming destination brings these elements into harmony. By equipping the world’s iconic venues with top-notch cameras, visual effects, and social streaming technology, Flymachine is pioneering the digital future of live events.
Fans get front-row seats right beside their friends thanks to picture-in-picture video chat overlaid on the best views of the stage. You can start a private room where you can mix the show’s sound with spatial audio from your pals to bounce between focused listening and commentary from your crew. Or, you can explore the rest of the crowd to run into friends or meet fellow fans. All the while, you get to support independent venues while enjoying jaw-dropping special effects and crowd visualizations. You’re in the center of the action awash in superb sound without anyone stepping on your shoes.
Attending events through Flymachine, you’re not limited to the tours coming to your town, or the artists willing to stream for free. Flymachine taps into the endless supply of in-real-life performances coming to iconic concert halls including some of Rolling Stone’s Top 10 Venues In The Country like NYC’s Bowery Ballroom and The Crocodile in Seattle. Artists gain an additional revenue stream by opting in to broadcast via Flymachine, allowing them to play to stadium-sized crowds from the intimate stages they prefer.
We spent the past year exploring the concert streaming space. Too many startups either forced artists to design and play shows just for streaming with no live audience to react to, cut venues out completely leaving performances looking drab and amateur, or ditched fans in asocial isolation. That’s why concert streaming hasn’t reached its full potential until now.
Building a company like Flymachine takes a special team with the experience to balance all the stakeholders in the notoriously complex music industry. You need someone like CEO Andrew Dreskin, the man who pioneered modern concert ticketing. He built TicketWeb, which was acquired by TicketMaster, and then TicketFly which was bought by Pandora. Andrew has spent 30 years in the business, from running the Beserkley Records store to managing the Virgin Mobile Festival to leading music at EventBrite and founding startups. That’s given him the empathy for artists, managers, labels, venues, and promoters that’s necessary to build a streaming destination where everyone wins.
Minutes into watching my first Flymachine show, I fell in love with a new band and ran into an old friend. I laughed with buddies about how much we missed live music, then dragged my little video window away to zone into a beautiful song. Soon I was wishing I could watch ballet or stand-up comedy with a similar experience. Luckily, Andrew and his amazing team have a vision to bring mediums beyond music to Flymachine.
Immersive. Social. Built so artists can expand access to their performances while growing their audience and business. That’s why SignalFire could not be more amped to support Flymachine on this audacious endeavor by leading the startup’s Series A financing that brings it to $21 million in funding (read more on TechCrunch). Other music industry legends joining the round include Redlight Management founder Coren Capshaw who manages Dave Matthews Band and Phish, concert promoter Another Planet Entertainment, and musicians like Mumford & Sons’ Ben Lovett.
Go check out Flymachine’s calendar of upcoming events. Regardless of where you are, we look forward to bumping into you at the next show.
We’re moving towards an experiential culture. People don’t end up on their deathbed lamenting “all those things I could have owned.” It’s “all those things I could have done!” Flymachine lets you do more. When you can experience culture surrounded by friends, you make memories, and URL becomes just as good as IRL.
Ok – curtains up. Break a leg, team Flymachine.
Creators get their own home on the web with site-maker Spore
Websites as a medium will live on longer than most of today’s apps (and humans).
“The web is the one place on the internet you can truly own—no middlemen. You can really tell your story, and it will outlast every channel” Shopify CEO Tobi Lutke told me. That’s why his commerce tools were built to give merchants a place on the web. And that’s why creators deserve the same. Spore’s website maker gives creators a home on the Internet that they truly own. Spore launches today (show them some love on Product Hunt), and SignalFire is honored to lead its pre-seed round.
The concept of “platform risk” is well-known to developers. When you’re dependent on some big tech platform that doesn’t share your priorities or incentives, you’re vulnerable. You live by their rules. If they want to cut you off from your audience, change the functionality you need, or charge you taxes for transactions or growth, you’re at their mercy. Just ask Zynga, the gaming empire built entirely on Facebook that saw its share price drop 85% in 7 months when the social network suddenly decided it didn’t want games in the News Feed. One algorithm tweak, and poof, Zynga’s virality evaporated. 9 years later, its valuation still hasn’t recovered.
The same could happen to creators. Right now, they’re in double jeopardy. Creators rely on social network profiles on Instagram, YouTube, TikTok, and Twitch for their internet presence and their connection to fans, which could be severed or locked behind ad spend at any time. They have followers but no direct contact info for their fans. To maintain their ability to reach people who already asked to see their art, creators burn themselves out feeding the fickle and inscrutable algorithms. Opaque and unevenly enforced content moderation policies lead creators to be suspended, shadowbanned, or booted entire, robbing them of their livelihoods and communities. If they try to walk away from the big social apps, creators are left with nothing.
Meanwhile, those social networks are built on iOS and Android, where Apple and Google collect 30% taxes on transactions. These operating systems aren’t helping creators get discovered, produce. Add up the fees from both, and creators often keep well under half of the revenue they earn while the platforms become hundred-billion and trillion-dollar companies. It’s labor exploitation at a grand scale that’s choking a huge new class of small businesses and the best opportunity for creators to turn their passion into a fulfilling profession.
Two trends and two problems for creators
I spent the last year since leaving TechCrunch to be an investor at SignalFire researching the creator economy. We discovered two big trends that beget two big problems:
- Creators are sick of pouring their hearts into building atop someone else’s platform, so they’re trying to move their top fans towards dedicated tools for community and monetization. But most of the tools are just more platforms that put their own brands first instead of the creator’s. It’s a laundry list of “Platform.com/CreatorName” links instead of a single, central “CreatorName.com”
- Creators are becoming founders, cobbling together an array of point-solution software and teams to run them. They need help with analytics, CRMs, ecommerce stores, content distribution, subscription payments, and more. But most creators can’t afford all these tools and teams, and don’t have the time to manage them. They want to make art and connect with their communities, not become web developers manually integrating fragmented APIs and datasets.
Spore lets creators build websites, not just profiles
After reviewing the pitches of tons of single-purpose creator tools, I found the answers to the platform risk and fragmentation problem.
Spore is a free, all-in-one solution for creators that lets them control their own destiny on the open web. With Spore, creators can easily design a self-branded website, collect contact info, send text and email blasts, grow a CRM, run chat rooms, review analytics, and accept one-off payments and subscriptions to content.
Since all of Spore’s tools are seamlessly connected, creators can spend more time making art and less time dealing with web development. It’s free to try, offers custom URLs and text messaging at cost, and creators keep 90% of their revenue since it’s built on the open web. That’s a lot more affordable than paying monthly fees for multiple separate tools, or the 30% to 45% taxes charged by social networks and mobile app stores. Spore only earns money when you earn a lot more.
Spore is launching today, but already combines the functionality of dozens of tools into powerful websites where creators’ brand comes first. Spore offers:
- Website creation: Squarespace, Wix, Weebly, WordPress
- Custom domains: GoDaddy, Namecheap
- Contact info collection: Forms, MailChimp, SurveyMonkey
- Fan CRM and scoring: Zoho
- Content analytics: Sprout Social
- Email newsletters: Mailchimp, Substack, Revue
- SMS blasts: Community
- Link hubs: Linktree, LinkInBio
- Link tracking and shortening: Bit.ly
- Chat and polls: Discord
- Podcast listening pages: PodLink
- Event listings: Eventbrite
- Merchandise (coming soon): TeeSpring
- Tipping/donations: CashApp, Venmo, PayPal
- Paid subscriptions: Patreon
How do these all work together? With Spore, you can choose a URL and instantly populate it with your branding, best content, social links, and color scheme without dealing with domain registrars or CSS. Perhaps the most important feature is the ability to prominently collect email addresses and phone numbers, that are loaded directly into the CRM from which you can send newsletters or automated content drops and event reminders.
When you create something new like a video, you can share it with a custom short-link that asks people to sign up, create a temporary banner promoting on your site, track its performance, and identify your super fans who engage most across all your content. Podcasts have special landing pages where fans can listen directly or get linked out to download on their preferred app. You can run chat rooms with polls where fans give donations or tips, or make your community or content exclusive to paid subscribers. And at any point, you can export all the contact info and upload it somewhere else like a dedicated newsletter service because you own the fan relationships.
Evolving with the creator economy
What’s especially remarkable is that Spore built all this since starting up in December. Co-founder and CEO Austin Hallock is the highest horse-power product developer I’ve ever encountered. He goes from idea for a feature to launch in mere days, which is exactly the superhuman agility you need to keep up with the rapidly-evolving creator economy.
Austin and I met when he pulled a legendary forgiveness-not-permission move. Instead of pitching me his startup, he showed me what it could by voluntarily sending me a website he’d already built for me on Spore called Constine.club. It let me run second-screen chatrooms for my Clubhouse shows while collecting contact info so I could ping people the next time I went live. A few months later, I already had thousands in my Spore community. When I request a feature like a podcast landing page, 48 hours later, he’s got it running on my site. By working directly with his early users, Spore built precisely the tool creators need.
That’s why I’m so excited to be Spore to be my first lead investment since leaving TechCrunch to join SignalFire. The $1 million pre-seed round is joined by some of the top creator-founders, including Twitch co-founder and rising TikTok star Justin Kan’s GOAT, leading Substack author Lenny Rachitsky, and newsletter bundle pioneer Nathan Baschez of Every. We’re also joined by Zynga founder Justin Waldron, Brat TV founder Darren Lachtman, Bleacher Report founder Dave Nemetz, and our friends at Canaan.
Spore’s mission is to help creators overthrow the gatekeepers, escape the taxes and algorithms, and build their own homes on the web. Social networks will come and go, mediums will rise and fall, but creators will always need a place to unify their community. With Spore, everyone can have the tools to turn their passion into their profession.
Rethinking the software selection and purchase process with TestBox
Enabling Customer-Led Growth
For decades, enterprise software has been sold, not bought. The software selection and purchasing process typically goes like this: a prospect lands on a customer website (which lacks transparent pricing info), they are forced to schedule time with sales, they get walked through a pitch and staged demo that lacks transparency and the ability to get their hands on the product, and then they spend weeks or months going back and forth discussing functionality, pricing, license, and more. On top of that a buyer isn’t just doing this process with a single vendor, it’s often 5+ different vendors!
Discovering what options exist for different types of software has already been tackled by companies like G2, Capterra, TrustRadius, Gartner, and many others. But, that is just the tip of the iceberg when it comes to completing a purchase. The most complex, time-consuming, and painful part of the process is the evaluation component which to date has been placed out of the control of the buyer. Even companies that do offer a trial or demo environment provide a completely empty sandbox which either needs heavy lifting by a buyer’s team to populate it with the appropriate data or is completely useless as it doesn’t give a sense of how the product would function under normal company demands.
TestBox is flipping the script and going back to first principles when it comes to evaluating enterprise software. They’ve envisioned a world where the buying process is customer-led and fully productized, putting the power back into the buyer’s hands and removing the many gates put in place by sales, sales engineers, and procurement.
They take the software evaluation process from months, down to hours by enabling the buyer and end users to test as many options as they’d like side-by-side in a unique sandbox environment. Each environment is pre-populated with customized synthetic data using OpenAI’s API to match the workflow and data needs of the customer creating a true apples-to-apples comparison which has never been possible before. What’s more, TestBox better aligns incentives as they are not trying to sell software that isn’t the right fit. They are agnostic to software vendor and are incentivized to help each buyer find the right piece of software for their needs. Additionally, they empower sales professionals to be the champions of their customers, building strong relationships and helping them achieve true success with their products.
Software spend in the US alone is over $500B annually and one of the most dramatic shifts over the past decade is the democratization of software purchasers. Historically, purchasing decisions were centralized among IT or Technology departments but as we moved away from monolith ERPs to a world where best-in-class point solutions have come to dominate, the power of the purse got distributed among the different teams that make up an enterprise. Now a CMO or VP Marketing is selecting which marketing automation system and social media management tool their team should use. A VP sales is choosing which CRM and call intelligence software meets their needs. And, a Head of Customer Success is selecting between Zendesk, Freshworks, and Hubspot for their helpdesk software. On top of this trend, we now see Millennials rising into management positions. These leaders don’t want to talk to sales, but want to self-serve and make their own decisions after testing each piece of software. This desire goes against existing software sales processes and requires a new set of tools to enable them to buy in the way that they want. TestBox is the first truly customer-led buying platform to put the power back in the decision makers hands.
The Right Team, The Right Vision
When we first met Sam Senior and Peter Holland, we knew that this well-balanced duo had big ambitions and the right complementary skill sets to rethink software purchasing. We were struck by their intuition about the need to reimagine and productize something that had never been streamlined and productized before. If they are successful, TestBox will create an entirely new category of software and champion an entirely new go-to-market strategy for software vendors to take a customer-led approach to their growth. This is a vision and mission that we are excited to get behind. We could not be more excited to lead Textbox’s Seed round and get the opportunity to join them for what is going to be an amazing ride in disrupting an extremely entrenched sales model and evolving the $500B software purchasing market.
Data scientist shortage? Replace them with Unsupervised
We are in the midst of a data explosion – almost everything we touch and work with today generates data. Reports estimate that in 2020, each person generated 1.7 MB of data every second through social media, email/other communication, videos, and that number is only increasing. 90% of the world’s data was produced in the last two years alone. The International Data Corporation estimates the global datasphere will grow from 64 zettabytes (1 zettabyte = 1 trillion gigabytes) in 2020 to over 175 by 2025.
And this explosion of data isn’t just in volume. It’s in complexity, all driven by new sources and types of data, new technologies, and changes in how consumers and businesses interact. These shifts came with the promise of unprecedented insights. If companies could stitch together and analyze this data, they could move from gut-based decision-making to being data-driven. This would help them deliver superior consumer experiences, significant top-line revenue growth, and increased bottom-line savings.
To capitalize on this, companies like Amazon, Facebook, and Google built huge, expensive teams to extract meaning from their data. But most organizations on tighter budgets have hit a roadblock: the data scientist shortage.
Had the world foreseen the simultaneous explosion in data volume and complexity as well as its lucrative application, we would have trained enough data scientists to make them readily available and affordable to businesses of all sizes. Instead, the relatively few with the skills necessary are in such high demand that salaries have ballooned and companies can’t hire enough. Turning data into insights is still highly manual today. The result is a problematic bottleneck, where companies waste time waiting for their slim data science teams to analyze new opportunities for improvement or miss them altogether.
The current analytics process often starts with a business user coming up with a hypothesis on what might be a meaningful insight within their data. They must then work with a data scientist to gather and combine that data into a well-structured format. Half of all data science work today is actually spent preparing data, and frequently ends with most of the data ending up pushed aside. After weeks to months of upfront work, data scientists can finally test if there was indeed a statistically significant conclusion in that data. If not, they must restructure the underlying data or start over altogether.
This manual process, combined with the talent shortage, has driven a significant gap between data science supply and demand. QuantHub estimates the 2020 data scientist shortage was 250,000. Businesses can’t wait for education to bridge that gap. They need a way to take data scientists out of the equation.
Enter Unsupervised. Unsupervised’s AI automatically analyzes their customer’s data and discovers the most significant opportunities and problems.
The platform does not require users to have data science backgrounds. It ingests raw data directly from sources, automatically prepares and analyzes the data, identifies any statistically relevant patterns, and ranks them based on impact to business KPIs (sales increases, customer churn, etc.). Business users can then directly review and operationalize those insights. Through this unprecedented volume and velocity of business insights, all business owners can find and respond to new opportunities and risks.
Unsupervised solves the data science crisis through AI, enabling non-technical business users to directly identify and respond to opportunities to optimize top-line growth, customer acquisition, and profitability. Unsupervised, plus a more affordable and plentiful business-team member, can replace the role of a data scientist.
We could not be more excited to be a part of Unsupervised’s $35M Series B and leverage our own AI expertise to support the team as they build an enduring automated analytics franchise.
SignalFire understands the value of data science because it’s what we’re built on. Roughly one-fifth of our team are AI PhDs, data scientists, and engineers. They work on constantly improving our Beacon technology which crunches a half-trillion data points to rank the skill and hireability of hundreds of millions of the most talented workers in technology. This is how we made 1000 job candidate intros to our portfolio in just one year. The team also refines our Beacon competitive intelligence engine, which sees about 4% of US credit card transaction data to help our portfolio companies assess macroeconomic trends, monitor competitors’ businesses, and optimize their own pricing.
But most organizations don’t have the resources to hire this kind of talent. With our investment in Unsupervised, we want to help democratize access to data science. We’re proud to support Noah Horton and his team at Unsupervised’s mission to help every company afford to better understand their business.