I’ve been obsessed with AI and its impact on our world for decades. This obsession led to several investments in the field, as I described four years ago in my blog posts on Applied AI: Beyond the Algorithm and The AI Paradox. So like many others, I have watched the evolution of generative AI and ChatGPT with keen interest.
At our Flybridge investment team meeting earlier this week, my colleagues asked how the explosion in the AI market compares to previous tech trends I have seen emerge over the last nearly 25+ years. Spoiler alert: I’ve been a VC for a looong time – see my reflections on 25+ years here).
While the move to the cloud (looking at you, MongoDB), mobility, and the rise of consumer social apps were all significant developments over the previous 15-20 years, they pale in comparison to the sudden change in the market over the last 12 months brought about, primarily by OpenAI and the launch of first GPT-3, more recently ChatGPT, and the rapid advances from other players such as Google.
In particular, I am struck by the speed of adoption and the incredible ubiquity and breadth of impact that the Large Language Models ( LLMs) and Generative AI already have. Today Groupthink is our always-on collaborative AI research assistant (picture a stateful marriage between ChatGPT, Google Search, and your favorite collaborative apps, and that’s Groupthink); we use the AI-powered no-code tool Blaze to build internal apps, Aiera provides me real-time transcriptions and AI-generated summaries of Wall Street events, Brighthire streamlines our hiring insights and processes with AI-powered interview summaries and transcripts, Proscia’s AI pathology platform will analyze my skin biopsy from the dermatologist, and my college-age son can use Teal to customize cover letters based on his resume and a potential job’s needs. And that is just an illustrative sample from our small Flybridge portfolio. Everything Everywhere All at Once, indeed.
(It should be noted that Everything Everywhere All at Once was an incredible movie and my clear Best Picture Winner winner from 2022.)
The closest analogy is the excitement I felt when I first opened the Mosaic browser to explore the worldwide web in early 1994. At the time, there was a rush to define companies as “web or dot com” companies, but that quickly became a meaningless distinction as every company leveraged the global connectivity and accessibility the web uniquely enabled to solve problems and create new markets. The same will hold for today’s new “dot AI” companies, as very quickly, there will be no such thing as an AI company, as the underlying technology will be leveraged across every new and existing application to drive unique value for customers and end-users. As with the first web applications, there will be value in being a first mover, but the real value will come from harnessing the underlying technical enablers in unique and new ways to solve real problems. For B2B founders, this will typically mean starting with a vertical focus, incorporating the AI into existing business processes and workflows, and in a way that is not AI for AI’s sake but rather with a laser focus on driving business value.
There is a lot of hand-wringing about whether this technical step function will change the nature of the economy, and perhaps not for the better. Similar concerns were raised with the rise of the internet in the mid to late 90s, but instead, it unleashed a creative explosion of new ideas, tools, and solutions. As my favorite movie of 2022 shows, there is an incredible opportunity to harness humankind’s unique creativity to build magical experiences and creative solutions to real-world problems. We could not be more excited to back this generation of founders harnessing the power of AI to build everything.
When a friend of Flybridge’s first introduced us to Roy Akerman and Ori Amiga, the co-founders of Rezonate, we were immediately excited and impressed by their insights, leadership, deep technical expertise, and ability to recruit talent. Roy was previously the head of the Israeli Cyberdefense Operations, and Ori led R&D for this unit, and both received the Medal of Honor for their contributions to Israel’s National Security. After serving their country, they both had successful careers in start-up cybersecurity companies, including Cybereason, where Roy launched several new products.
We also loved the problem they were targeting: protecting the most critical cloud systems by eliminating attackers’ opportunity to breach cloud identities and access. Securing identities and, therefore, access, for both humans and machines is the key to protecting the cloud. Yet, cloud infrastructure’s growth, complexity, and ever-changing nature make this a difficult problem to crack. Rezonate’s disruptively simple approach is to, in real-time, discover, analyze, profile, and protect every identity, user, and resource across all cloud assets, preventing and stopping attacks quickly. We introduced the company to several potential customers in our diligence and received nothing but positive feedback on their approach. The cloud security market is large and growing fast, reflecting the importance of protecting cloud assets. Analysts estimate total spending of $33B today and project a growth rate of over 18% per year to $106B in 2029.
With strong founders with unique product insights into a significant, critical, and timely market opportunity, we were thrilled to co-lead the company’s seed round alongside State of Mind Ventures, toDay Ventures a Merlin Ventures seed fund, and several prominent angel investors. Since our investment, the company has made great strides and executed exceptionally well — building an exceptional team, developing the product (screenshot below), landing several design partners, and converting them into paying production customers.
Rezonate recently came out of stealth mode, and has been featured in TechCrunch, VentureBeat, and Forbes. We are confident in the future of this talented team and their innovative solution to cloud security!
Conventional wisdom for founders of early-stage venture-backed companies is that it is best practice to send out monthly investor updates – and we agree. We see a significant correlation between success and the companies whose founders maintain the discipline to follow this best practice. Much has been written about what format to use and why this is important for investors (here are a couple of links for reference here and here), but very little is written about why it is important for founders and their teams in the first place.
This distinction is important because while it might be easy to fall out of the habit of doing something for someone else, it’s much easier to maintain a habit when it is for you and the objective of having your company and team to be as successful as possible. Centering the monthly update and tying it to your bottom line is a game-changer. To keep it simple, keep in mind the Triple-A rubric:
Alignment: the pace of a start-up can be frenetic, with constant on-the-fly decisions. Taking a moment each month to pause, and reflect on the company’s goals, accomplishments, strategy, tactics, and needs is important for you as the founder to make sure you are focusing on the most important issues and for your team to share and understand that same focus. As one of our founders, who has written a monthly update every month since early 2020 from pre-launch and $0 in ARR to over $8M in ARR, says “while the subject line says Investor Update, I am really writing for me. It allows me to pause the first Sunday over every month and reflect on the business – what we have done well, what needs improvement, where there are gaps in my team, and what I need to make sure I personally focus on in the coming month”. This founder uses the same content for their All hands to make sure the team is equally focused and aligned.
Accountability: as a leader, you know the importance of accountability in terms of driving results, focus, and creating a high-performing team and while this most often comes from within, using external accountability to build internal accountability can be a powerful force for action and results. As one of our founders said, “I don’t think founders should rely on others to hold themselves accountable. But it still feels bad to write the same thing twice in an e-mail. The practice of sitting down to send an update builds in internal accountability.”
We firmly believe that start-ups win because they execute more rapidly and effectively than larger organizations, and if knowing that you are reporting on results to a broader audience than just yourself on the margin increases the likelihood that a key product feature is shipped on time, or sales to close as forecasted, is only goodness. If your team also knows that you are reporting more broadly, it increases the likelihood that they too will share the same degree of urgency. Finally, the monthly part of the month update, versus quarterly, reinforces this focus on speed of execution.
Access: as a small team, the extended network of advisors and investors can be invaluable in generating sales leads, potential partnership opportunities, candidates to join your team, how to compensate them, and insights into the key issues you are wrestling with at any point in time. When you formed your cap table you likely thought deeply about why each investor was involved in the company, and the monthly update can be one important way to realize that potential. As another founder noted, “As a founder, I’m confident that I have the most context to make decisions. But realistically I will never see as many startups as an investor has, and investor pattern matching is an important input to take into account. If an investor has seen 90% of successful startups do X in a similar situation, the founder should have a solid reason to not do X.” Further, there is significant research on people and companies that seem to regularly “get lucky”, but in reality, that luck is a result of building relationships, showing gratitude, and being open to new ideas and connections, all of which is facilitated by the monthly update.
The most common failure pattern we have observed over the years is not not starting to send our monthly updates but rather stopping when things are uncertain or going less well than expected. This is understandable – no one likes to share bad news and to be transparent with issues and uncertainty, but this is exactly when your investors and advisors can be most supportive as they have likely encountered similar situations in the past or may be able to open doors, make connections, ask questions that can be helpful in navigating through the uncertainty or just provide emotional support. Two anecdotes in this regard, one positive, one negative:
We were pre-seed investors in one company that found its initial product-market fit was just not there. They shut down this focus, iterated, explored, went through a “summer of despair”, and eventually landed on what seemed like a promising new focus. Never once did they fail to send out a monthly update. When the new direction started bearing early signs of fruit just as cash was running low, we were thrilled to invest more in the company to give the time and resources needed to get to milestones that allowed them to raise a large seed round from a new investor. Why? We obviously believed in the new direction, but equally importantly we had been part of the entire journey and saw just how effectively the team was able to execute during difficult times.
We were small pre-seed investors in a company where the founder “went dark” and stopped sending updates until finally reaching out to let us know that the assets of the business had been sold to another company for essentially nothing even though based on the last update things seemed to be going well (financing fell through). As it turns out, the CEO of the acquirer was a close (non-obvious) friend of ours, and yet because we never knew of the challenges, we were not able to have any impact on the result. Could this relationship have been leveraged into “getting lucky” with the acquisition at a higher value, we will never know but think that perhaps yes. In other words, you never know what and who your extended family of supporters knows unless you ask.
A last and final incentive, if the above was not enough. Sending monthly updates is time-efficient. When you stop sending updates, it increases the likelihood of multiple inbound calls and, especially if you have a large-cap table, you will spend far more time doing one-off calls than the time it takes to share the same information with everyone consistently.
In terms of the format and approach to monthly updates, we will not rehash the existing materials out there, but encourage you to:
Keep the format simple and consistent. It is much easier to send every month if you are not starting from scratch.
Block out time and stack it with other administrative tasks so you both get it done and don’t interfere with important sales or product work.
Share issues and things that have not gone well. This increases trust and increases the likelihood of generative conversations with your investors and advisors.
Always make asks/have a “how you can help” section. If you are heads down executing, it is ok for this to be “no asks this month”.
Thank people who have helped in the prior month. This increases the likelihood that others will help in the future.
At the bottom, rehash the company’s mission and what you do as noted in the linked examples above.
So send your monthly investor updates. Not for us, but for you and your success.
Leading-edge software developers are amazing – yet incredibly demanding – early adopters. For products and platforms that increase development velocity, remove complexity, and drive performance and scalability, their initial support is a leading indicator of future success. Companies that channel this early support into creating a passionate, engaged, developer community build better products, see stronger adoption, and ultimately build better businesses than their non-community-driven peers. This is an important investment theme for Flybridge and one we have seen play out successfully with our prior investments in companies such as MongoDB, which is now a $30+B value public company whose industry-leading database has been downloaded over 200 million times from their website, and Firebase, which now has more than 3 million apps using its services and in which we were seed and Series A investors prior to their acquisition by Google in 2014.
Fast forward to 2021 and one of the fastest-growing developer communities is forming around Appwrite. Initially developed by Founder and CEO, Eldad Fux, as a passion project to solve his own problems (as all the best developer platforms are), the Appwrite community has exploded in the last 9 months growing to over 50K members and over 375 code contributors across the globe. Developers love the platform, which now has over 13,000 Github stars, making it one of the fastest-growing repos on Github, and usage is up 24 times in the last 6 months. The passion for and engagement with Appwrite can be seen in their most recent release, where open source contributors outnumbered maintainers and over 100 community-driven pull requests were merged into the main branch.
Appwrite is a secure open-source backend server for web, mobile & flutter developers, that is often referred to as an open-source version of Firebase. Google has been an excellent steward of Firebase, but nearly 10 years after its initial release which enabled real-time applications, and after integrating several acquisitions, we and the Appwrite community believe there is an opportunity to create the leading backend service for the next 10 years.
Specifically, Appwrite was written from the ground up to be the best backend as a service on the market, with consistently designed services that drive a better developer experience and APIs that are designed to work well as a whole, yet with the flexibility to be consumed separately. All the protocols are ones that developers already know, which shortens the learning curve and the time to wow. Finally, in today’s multi-cloud, privacy-aware, and security-focused world, Appwrite can be hosted on any infrastructure, location, and platform which allows application developers to control their data, users’ privacy, and comply with local regulations.
Given this success, we were thrilled to co-lead the company’s recently announced $10M Seed round alongside Bessemer, Ibex Investors, and Seedcamp. The resources will be used to expand the team (careers page here) and drive the roadmap, including releasing Appwrite 1.0 and the Appwrite Cloud service as well as deepening the platform’s database, storage, authentication, and functions services, all while being responsive to new ideas brought forward from this incredible community. We look forward to the journey!
Venture capital partnerships such as ours are small and hire new partners infrequently. As a tight-knit, cohesive partnership that very much works together as a team, getting this right is especially important. A year ago, as we were early in investing out of our 2019 fund and looked forward to launching a new Flybridge fund 12-24 months from now, we decided to add a new General Partner to our team. We knew it would be the most important decision we would make this year.
We cast a wide net, hired a recruiter, reviewed 100s of candidates, and met with dozens. Our criteria were simple: we were looking for someone that was wildly curious, with tremendous investment judgment, who approached venture investing with innate founder empathy, brought with them a deep appreciation for the power of community and the connections to back that up. Importantly, we wanted someone who would fit seamlessly into our team – valuing our long history of working together while challenging us to lead in new directions.
With today’s announcement that Anna Palmer is joining the Flybridge team as a General Partner, we (immodestly) crushed this decision. Jeff, Jesse, and I are beyond thrilled to welcome Anna to the Flybridge Family.
I first met Anna in late 2012 when she launched her first company, FashionProject, out of the TechStars community. Immediately struck by her raw intelligence, creativity, and passion for making a difference through entrepreneurship, we stayed in touch as she built FashionProject into the industry leader in online designer clothing donation, building a community of tens of thousands of members and non-profits across 36 countries. But it was not until after the election in 2016 that we began to work together as collaborators and partners.
Anna identified a significant unmet investment opportunity in companies founded by women and wanted to partner with the Flybridge team to form a venture fund focused on investing in female-founded companies pursuing billion-dollar opportunities. Aligned with her vision and inspired by her ability to galvanize change, we jumped at the chance and formed XFactor Ventures.
Anna created XFactor’s unique model: we are a team of women, other than me, that are all current founders of venture-backed companies that are investing at the earliest of stages behind the next generation of founders seeking to build transformative companies. As active founders ourselves, we know first-hand the ups and downs of building a company and seek to support our portfolio founders with capital and the connections and mentorship to navigate the company building journey. We launched XFactor in July of 2017 and have since grown our community into an investment team of 22 founders in 6 cities and nearly 60 portfolio companies across two funds with over 80 amazing women founders and co-founders.
As we worked together over the last four years, in addition to seeing her drive in creating and building XFactor, we saw her instincts as an investor as she personally led seven investments for XFactor — including in Chief, Zubale, and MixLab — that are all performing incredibly well. Anna is extremely curious, can see connections from one industry that apply to another, has an excellent feel for important trends in the marketplace, and a natural sense for what companies will drive outsized value in the future. Not to mention she did all of this part-time while also launching, with a co-founder and our investment capital, her second company, Dough, from our offices.
Fast forward to September of this year. Driven by Anna and the investment team’s talents, the breadth of their networks, and the depths of their insights, XFactor’s success proved yet again that in early-stage venture investing, relationships and expertise are all that matter. XFactor’s network and expertise are very complementary to ours and there was clearly an opportunity to align our investment efforts more closely while still preserving the power of XFactor’s unique model. Thus, we leaped at the chance to add Anna to our team when she decided to become a full-time investor after Dough had reached a level of maturity such that she could hand over the CEO reins to her talented co-founder, Vanessa Bruce. Starting work 24 hours after saying yes, Anna joined to help us kick off our annual Founder’s Week, and in partnering together full-time over the last two months, it is like we have been working together for years…which, of course, we have been.
Anna will focus on the full range of B2C and B2B opportunities with a specific interest in community-driven companies, commerce 3.0 (logistics, discovery, payments, social commerce, small business solutions), marketplaces, and the everyday economy while also continuing to drive XFactor Ventures forward. You can read more on her Medium post here and follow her on Twitter here, but on behalf of the entire Flybridge community, please join me in congratulating Anna and welcoming her into our team!
Massive winners define great venture capitalists and great venture capital funds. The best investors fully internalize this power-law of venture returns and seek to back companies that can become “outliers”. Massive wins are all that matters in driving outcomes.
A key to investing behind the best companies is to identify macro market trends early and to ride the waves of growth they create. High growth companies need the wind at their back, so investing early behind emerging trends that develop quickly creates an environment for young, growing, businesses to flourish.
To be a great investor, you need to master the cycle of Seeing-Selecting-Winning-Investing-Supporting-Harvesting. “SSWISHing means you need to see many opportunities, select the best ones, win your way into hot deals, support your companies’ growth, and navigate a path to generating liquidity from your investments. Each stage feeds off the others.
The best-expected-value returns are most likely the companies in your portfolio that are killing it, so lean into your winners with more capital. Smart follow-on decisions should be married with a starting portfolio of more, rather than fewer companies, to account for the inevitable randomness in returns and performance.
I would like to thank my Flybridge partners Jeff Bussgang and Keegan Forte; all my XFactor partners, but especially Danielle Morrill, Aihui Ong, and Anna Palmer; the Columbia Business School students in Angela Lee’s class, “Foundations of VC”, that saw an early presentation on this topic; and my family for their collective input to and inspiration for these posts, although as always any mistakes and omissions are all mine.
Earlier today we launched XFactor Ventures 2, a pre-seed and seed stage venture fund. The fund, with just under $9M in commitments including a portion from Flybridge, will invest $150K each in 50+ pre-seed and seed stage companies with female founders targeting billion-dollar opportunities.
When Anna Palmer, the rest of the Flybridge team, and I had the idea for XFactor Ventures two years ago our thesis was a simple one: putting checkbooks in the hands of existing female founders would not only help more new female founders launch and build their companies but also give the investment partners the opportunity to translate their deep networks and expertise into strong investment returns. Despite launching with a lot of confidence, we had no idea that it would succeed to the extent it has. As a result, we are pleased to scale up the effort – more investment partners, more companies, and more capital per company – with XFactor Ventures 2!
XFactor was formed out of a combination of frustration and belief. Frustration that less than 20% of the companies receiving venture capital funding have female founders and a belief that companies with diverse founding teams will outperform in the market. We also had a hypothesis that our unique investment team, which is comprised entirely of existing female founders of venture-backed companies would be in a preferred position to identify new high-potential, early-stage, companies with female founders and to provide not just capital, but also mentorship, guidance, and connections to help our portfolio companies succeed.
In keeping with our entrepreneurial spirit, the first fund was a true MVP that we stood up fast, learned from, iterated on quickly, and succeeded with, resulting in investments behind 28 companies, all with passionate, persistent, and talented female founders. We thought that there was a gender gap in the venture industry, but the level of interest and the quality of investment opportunities blew us away. This portfolio was selected from the nearly 1,500 new companies we have been introduced to and is diverse across sectors (54% B2B, 25% B2C, and the rest health-tech and FinTech) and geographies (36% Bay Area, 32% NYC, the rest are based in 9 other cities).
As we formed XFactor 2 to build on this success, we had three goals. We wanted to:
Expand our investment team to address sectors and geographies in which we see significant opportunities
Support more companies
Invest more capital behind each new company.
The investment team for XFactor 2 will have 23 investing and operating partners, up from 10 in XFactor 1. All the investment partners, other than me, are existing female-founders of venture-backed companies. Immodestly, the team is impressive and I am regularly wowed by the depth of their expertise, their passion for our mission, and the breadth of their network. Our portfolio companies, as a result, benefit not only from the skills and mentorship of their specific sponsoring partner but also from the collective talents and experiences of the team. The full investment team is listed below and linked here, but the high-level details include:
The partners have founded 28 companies that employ thousands of people and have raised over $550 million in venture capital. The new team includes 5 YC grads, 5 Fortune 30 under 30s, 9 MBAs, 2 JDs, 2 published authors, 1 PhD, and 1 Emmy award-winning producer.
We added an entirely new team in Los Angeles, a vibrant and female-founder friendly market, and a partner in Seattle, Amy Nelson, who is also, excitingly, the founder of an XFactor 1 portfolio company. As a result, we now have a strong nationwide presence in the Bay Area, Boston, Denver, Los Angeles, New York, and Seattle.
We added expertise in the healthcare, FinTech, AgTech and frontier tech sectors.
Finally, all of the partners in XFactor 1 are returning to XFactor 2.
Our investment model in XFactor 2 will remain the same. We seek to back the most promising female-founded companies pursuing billion-dollar opportunities. We invest early, like to be the “first-check”, and will make a one-time investment of $150K, up from $100K in XFactor 1, in each company. We do not make follow-on investments as we have found this allows us to be the “first-call”, forming open, honest, and trusting relationships with our founders. With committed capital of $8.6M, XFactor 2 will invest in 53 companies, up from 29 in XFactor 1.
Despite these changes and growth, what remains are the frustrations and core beliefs. Female founders are still woefully underrepresented in the ranks of companies receiving venture capital funding. In 2018 17% of venture dollars globally went to companies with female founders, and at the seed stage, for the last five quarters, just under 20% of total funding went to companies with female founders. Depressingly, this is largely unchanged since we launched in 2017.
Our conviction for the investment opportunity has only increased over the past 2 years. We are constantly wowed by the tenacity, resilience, and talents of the female founders we see starting companies and, of course, particularly love the 28 founding teams we have supported with our first fund. The opportunities being pursued by female founders are diverse and don’t conform to stereotypes. We have in our portfolio AI companies, FinTech companies, SaaS companies, Healthcare and medical companies, Future of Work platforms, Consumer apps, and E-commerce brands, and all are seeking to build businesses of significant scale. We are excited and thrilled to have the opportunity to back an additional 50+ such inspirational teams from XFactor 2 in the coming years.
Are you a female founder with the XFactor looking for funding? If so — we want to talk to you! Please find us online at XFactor.ventures, follow us on Twitter or reach out via email to firstname.lastname@example.org. As we believe in diversity and inclusion of all people, of all genders, races, ethnicities, sexual orientations, educational backgrounds, religions, abilities, socioeconomic backgrounds, immigration statuses, and more, we will review and consider all opportunities that meet our investment criteria.
The investing and operating partners in XFactor Ventures 2 are:
Nobel Prize-winning Economist Robert Solow once quipped that “You can see the computer age everywhere but in the productivity statistics”. This famous observation has become known as the Productivity Paradox – the conundrum that economists face when trying to explain how is it that productivity in the US slowed down just as investments in information technology exploded in the 1980s and 1990s.
Today, we face a similar paradox, the AI Paradox. Just as corporations are investing billions of dollars in AI infrastructure, the actual impact and absorption of AI in the enterprise seems relatively muted.
Earlier this month, the MIT Technology Review published an excellent article entitled “This is why AI has yet to reshape most businesses”. Some of the themes rhymed with our recent post about the potential for Applied AI companies, but also the real adoption barriers. It is striking that, although AI has been a central area of focus for may enterprises for years, actual adoption has lagged the hype. PWC recently conducted a survey of 1000 enterprises that are currently implementing or investigating AI and learned that only 20% plan for enterprise-wide adoption in 2019. Many projects are thus still stuck in pilot purgatory.
This dichotomy between promise and reality points to the power of Applied AI startup companies that focus intensely on the path to the adoption, and absorption, of AI into the enterprise. Internally, we are calling this type of startup “AAA” grade – Absorbable, Applied AI.
Here’s why the approach of AAA startups matters so much in driving AI adoption::
First, as the article points out, the “initial payoff is often modest” of AI projects. Thus, we think it is important for Applied AI companies to “manage expectations along the way, as many Applied AI use cases falter based on overselling the potential and customers expecting too much when in reality improvements come incrementally over time”.
Second, the article mentions how if “companies don’t stop and build connections between such systems, then machine learning will work on just some of their data”, which strikes us as an approach a company focused solely on developing narrower, application-specific solutions can take as they can often derive insights gleaned from data that reflects “the real-world variance and dimensionality of the problem space” and can work aggressively with “input from domain experts to identify the logical gaps that exist and how to fill those gaps”.
Third, as “Ninety percent of the work is actually data extraction, cleansing, normalizing, wrangling”, this provides an advantage to third-party Applied AI companies, as opposed to internal DIY AI efforts, as the third party application provider–which are typically cloud-based platforms that scale across customers—is able to leverage this data wrangling cost across a wide swath of enterprises.
Finally, the article points to several aspects that impede adoption including how end users need to be “attuned to how AI works and where its blind spots are” and how “In order for them to trust its judgments, they needed to have input into how it would work” which is why we feel it is critical for Applied AI companies to combine domain expertise with technical expertise, carefully collect the domain-specific requirements and use cases, use those requirements to “instantiate the models into a broader application that fits into customer’s broadly defined workflows”, and make transparency and explainability a core feature of the application, not an afterthought.
If AI startups can apply these AAA techniques, they are going to continue to achieve superior customer traction as compared to their competitors. And, in doing, attract plenty of attention from AI-focused venture capital firms like Flybridge!
One of the primary areas of focus for Flybridge over the years has been to be the first institutional investor behind companies looking to transform the enterprise technology landscape with modern software. Given the explosion in the volume of data being generated globally, this theme has led to investments in companies such as MongoDB (databases) and Nasuni (storage) that operate at the data infrastructure layer of the enterprise tech stack.
More recently, we have been investing in further advances in data management, analytics, machine learning, and artificial intelligence. While the potential for artificial intelligence has been written about extensively, what is less well understood is that the algorithms and underlying tools are only a fraction of the value and are unlikely to be a source of long-term differentiation. Fully realizing the power of AI requires a deep understanding of the domain and the specific workflows that AI will seek to improve and optimize. In other words, the application layer of AI ultimately drives the business value. And we believe the window of opportunity for the AI application layer is now.
This evolution from platform to applications is not an uncommon one: when a new technology platform is immature and not well understood, there is a lot of room for innovation at the underlying technology layer, but as the platforms mature the application layer is where value accrues. For example, in the PC era, once Windows and its associated tools were well developed, apps accumulated a huge amount of value; and similarly in the early Internet era, once the browser, server, and app server infrastructure were well established, apps became super valuable.
This “Applied AI” investment thesis resulted in four new investments by Flybridge in 2018: Aiera, which is using AI to drive fundamental equity analysis; Kebotix, which is using AI to discover and create advanced chemicals and materials; Looka, which is an AI-powered graphic design platform; and Proscia, an AI-powered digital pathology solution. We also made follow-on investments in our existing, scaling, Applied AI portfolio companies Bitsight, Bowery Farming, Datalogue, and DataXu.
Given the breadth of this emerging portfolio, we thought it would be helpful to expand on what we look for in Applied AI companies and some of the keys to success in building a company in this exciting field. We believe that it is important to:
Go Old School. Opportunities for Applied AI companies lie outside of the markets targeted by traditional web-scale companies. As Andrew Ng recently observed, “a lot of the stories to be told next year  will be in AI applications outside the software industry”. Many of these markets, such as Real Estate, Finance, Healthcare, Oil & Gas, Agriculture, Manufacturing, and Logistics, have the advantages of being A) extremely large, B) where innovative AI driven approaches can drive massive levels of improvement versus the status quo, C) where potential customers may not be able to access AI talent on their own, such that build versus buy is less attractive, and D) not being an area of focus of the Googles and Baidus of the world where their massive troves of data can be a source of significant competitive advantage.
Combine Talents. The most successful teams in Applied AI will have a unique combination of an understanding of the domain and the technical capabilities to realize the vision. Even more specifically, it is doubly helpful if one of the founders was formerly a practitioner in the field. For example, Dawson Whitfield, the founder of LogoJoy, was previously a top-notch graphic designer himself; Ken Sena, was a top-ranked equity analyst before founding Aiera, and Kebotix co-founder Professor Alan Aspuru-Guzik holds a Ph.D. in Chemistry and is a leader in the field of computational chemistry. In other words, AI experts will do better when teamed up with someone that comes from the field in which they are seeking to operate.
Drive continued technical innovation. Given how quickly the field is advancing, a deeply technical co-founder who is up to speed on, and willing to continually learn about the latest advances in AI, and see the application of new approaches to the problems their company is seeking to solve is essential. Whether it is “few-shot” learning approaches, ensemble models, GANs, CNNs, transfer learning, explainability, and a myriad of other developing techniques, knowing and understanding the strengths, weaknesses, and applicability of different approaches is critical. We often see the domain expert mentioned in point 2) renting or borrowing their AI expertise in the form of advisors and part-time experts, but this approach is not good enough given the need to have a tight feedback loop between market-driven customer needs and the AI-driven technology insights and art of the possible.
Create Data Network Effects. The most successful companies will have a clear understanding and angle on how to start and continue to spin the data network effects flywheel. Generally, this requires having access to initial datasets that can begin the model building process, and a well thought out and focused strategy on how to increase the quantities of data available for analysis. The initial data sets, which Proscia refers to as “inorganic data”, might be acquired, and are used to overcome the cold start problem of training a new model from scratch. In contrast, “organic data” that comes from the ongoing use of the platform can help hone and refine the algorithms over time. Taken together, this means the cost of data should decline over time because organic data is typically free (or even negative if you can get users to pay you for the service delivered while the data is collected). In the pursuit of data, it is important to remember that the sheer volume is not always inherently better. Yes, size matters, but quality matters more. The data should reflect the real-world variance and dimensionality of the problem space and a data strategy should incorporate input from domain experts to identify the logical gaps that exist and how to fill those gaps. Further, when assessing a technical team (per point 3), we believe it is important that they know how to build an AI infrastructure that can be monitored for changing performance and updated accordingly as the scale and scope of the datasets increase. For example, when Aiera first started making buy-sell calls on stocks, they only did so on 16 companies based on a model that analyzed 10,000 documents a week from 300 data sources. Today, they cover nearly 2,000 securities with a model that analyzes 500,000 documents a week from 22,000 data sources. Perhaps not surprisingly, the accuracy, breadth, and duration of their buy-sell calls increased significantly over this time.
Absorb The Algorithm. The specific algorithms and AI techniques themselves are not the sources of defensible value so the most successful AI companies will instantiate the models into a broader application that fits into customer’s broadly defined workflows. We call this “Absorbable AI”, which means customers can incorporate the AI into their business and realize the benefits of the operational insights. Successful AI Applications need to not only explain why the model is generating certain results (and, importantly, explainability also helps understand and highlight bias such as gender-based or racial bias), but also integrate into the customer’s business in a logical and systematic way. It’s also important to manage expectations along the way, as many Applied AI use cases falter based on overselling the potential and customers expecting too much when in reality improvements come incrementally over time. These application and process skills are often found coming from the more traditional application development space in fields such as UX, visualization, workflow/BPM, and integrations.
Craft the Business Model. Thinking through the business model of a company is critically important. Depending on the domain, the openness of customers to new approaches, their willingness to pay for innovation, and the scale of the level of AI being incorporated, the best way to realize the value of an Applied AI company could be by selling an application that makes human work more efficient and accurate–an end-to-end automation stack that replaces humans–or it could be by selling a complete product. For example, our indoor farming portfolio company, Bowery, leverages a significant amount of AI to drive efficiency and quality in their operation, but they decided the best way to realize the value of that AI was to sell incredibly tasty, locally grown, pesticide-free green vegetables versus selling an AI-powered Farm Operating System to other growers. A similar example would be Tesla, where the vision is the sell a complete, AI-powered, autonomous vehicle, as opposed to say Cruise, which chose to realize the value in selling the application (and the company) to other automobile producers.
Points 5 and 6 can be better visualized in the following matrix:
With the continued explosion of data availability, advances in AI techniques, and the accessibility and performance of computing (GPU) cycles, we believe the trend of AI as the next great application enabler will continue for some time, and we look forward to finding more Applied AI companies with passionate domain experts and technical founders to invest behind in the coming year.
Thanks to my partner Jeff Bussgang, our advisor Harini Suresh, David West of Proscia, and Bryan Healey of Aiera for their input and insights in developing these thoughts.
This month, Crunchbase released 2018 funding stats for companies with female founders under the encouraging headline; “2018 Sets All-Time High For Investment Dollars Into Female-Founded Startups”. While that statement is factually accurate — $38.9 billion was invested in companies with a female founder in 2018, up from $19.8 billion in 2017, which represents a 3 point increase in the percent of total dollars invested from 14% to 17% — a deeper look is less encouraging.
If you remove the $14 billion Ant Financial financing, just one investment, the dollars decline to $25 billion and the percent of total dollars declines to 13%, which is down year over year. Similarly, by the total number of investments, there was a decline from 15% to 14%. The data from Pitchbook, by way of Fortune, tells a similar story of limited progress.
These industry-wide stats are in contrast to the investment opportunities I saw in 2018:
125 of the 260 companies I met in 2018 for a focused “new investment pitch”, were with a company with at least one female founder. That’s 48%. Not quite parity, but very close.
100% of the 16 new investments made by XFactor Ventures in 2018 were in female-founded companies. XFactor Ventures was created in July 2017 in conjunction with an amazing team of women who are currently leading successful venture-backed businesses. It is our collective goal to invest in early-stage female founders pursuing billion-dollar opportunities. Of these 16 companies, 9 have all-female founding teams and in 13 of the 16 companies, the female founder is the CEO. If this data was included in the Crunchbase article linked above, XFactor would fall as the second most active venture investor in female-founded startups — below NEA but above Founders Fund, Social Capital, and Sequoia.
40% of the new investments Flybridge has made in the last 18 months (since the launch of XFactor), have had a female founder — an increase of 13% from the preceding 18 months.
While the available data shows it was not the case for the industry as a whole, for me, it’s clear that 2018 was a strong year for female founders. For new investments, venture capital has always been a network, relationship, and focus business but since the launch of XFactor, we’ve noticed a shift — our networks have expanded, driving a significant increase in the volume and diversity of the investment opportunities we’ve seen. In 2019 we expect this momentum to continue and even pick up speed. Also, stay tuned for more from XFactor as we are actively expanding the investment team and will announce a second, larger fund in the early coming months.