Our first full quarter as anything more than an exciting idea has been a whirlwind. At the heart of it all, thanks to your partnership, we started work on building the companies that are going to transform the technology industry and the broader economy as a whole. In this first investor letter, we wanted to provide an update on our initial investments, and also to restate our vision for the Factory.
“There is a data-centric research agenda inside AI. It’s intellectually deep, and it has been lurking at the core of AI progress for a while” “The Road to Software 2.0 or Data‑Centric AI” by Chris Ré (https://hazyresearch.stanford.edu/data-centric-ai)
The model has long been the center of attention within AI/ML, but increasingly the industry is recognizing that the data often matters more, and is the key to unlocking the next wave of innovation. This vision was originated by our co-founder Chris Ré and students in his lab at Stanford, and his research continues to be the foundation of everything we do. Their work has already been deployed into production through Apple’s Overton project, which monitors and optimizes machine-learned products, through YouTube’s leveraging of different data modalities, and through Google Adwords’ use of Snorkel for weak supervision. These are early examples of how some of the most sophisticated teams in the industry have started to take a data-centric approach to their work. We expect to see this accelerate over the next three to five years, and leap from the Apples and Googles of the world into Financial Services, Healthcare, Retail and Manufacturing. Bridging this gap requires radically different systems and a new theory and practice for maintaining them. The startups taking on the challenge of building this new stack, or building applications on top of it, will find their home at the Factory.
Financial & Portfolio Overview
We closed our initial fund, Factory HQ Fund I, in Q2 2021 with committed capital of $75 million. By end of June 2021, we had invested approximately 12.6% of that in six exciting investments, typically alongside bigger funds such as Walden International, Blackrock, Lightspeed, Addition and others. Each of these investments is consistent with the approach we presented during fundraising: They represent various elements of the Data-Centric AI stack, and have an opportunity to build a large and valuable business through dominating the market that will develop around it. We believe that by investing capital AND working with them on their Technical Vision, Product Management, Go-to-Market, Operations and Recruiting, we can help reduce technical and execution risk, and accelerate each company through their key milestones. We choose to work with deeply technical founders and also look for cultural fit represented by an appetite to work with the Factory’s “sleeves rolled up” model. Some are candidates for IPO, while the others are likely to see an earlier exit through acquisition. Our approach is to reserve capital so we can continue to invest in subsequent raises, though we may choose to sell shares in later rounds, or hold for the journey through to IPO. This decision will be made on a case by case basis.
The deals we closed (listed below), and the ones we chose not to invest in came to us through the extended network of the Factory Co-Founders and LP’s. We continue to see incredible inbound deal flow thanks to the reputation of everyone involved, and driven by the excitement of the startup founders to work with the Factory team. We see no sign of this deal flow slowing down (quite the opposite!) and there has been no need for us to do any outbound deal sourcing work so far.
Voltron Data is building the default, hardware-optimized foundation that simplifies and accelerates data analytics workloads across programming languages. Founded by the pioneers behind Apache Arrow (led by Wes McKinney), RAPIDs (led by Josh Patterson) and Blazing SQL, the company is executing on a roadmap to be the default data analytics platform for at-scale enterprises.
Galileo is building the data quality platform for data-centric AI. Founded by proven AI/ML technical leaders from Uber (Michaelangelo) and Google, the platform is empowering AI teams in Square, Lemonade and others with the continuous ML data quality critical to achieving superior results, faster than ever before.
Predibase is on a mission to make machine learning simple to use for anyone who speaks SQL. Founded by the creators of the wildly successful open source Ludwig and Horovod projects for ML deployment, the company’s low-code, declarative machine learning platform dramatically reduces the pain of building and operationalizing business impacting ML models.
TinyStacks is helping developers build production-ready services on any cloud without having to interface with the hundreds of cloud services. Founded by the tech leads of AWS DynamoDB, Redshift and Glue, the fast moving team is bringing to market an intuitive experience for building and operating compute workloads using intelligent IaC (infrastructure-as-code) automation.
SambaNova Systems is building the industry's most advanced systems platform to develop and deploy next generation artificial intelligence and data intensive applications from the data center to the cloud and the edge. SambaNova’s DataScale is optimized for data flow from the algorithms to the silicon, enabling enterprises to bring new services and products to market faster than today's state of the art solutions. The company was founded in November 2017 in Palo Alto by industry luminaries, hardware and software design experts, world-class innovators from Sun/Oracle, and Stanford University.
Snorkel started at Stanford with a simple technical bet: that it would increasingly be the training data, not the models, algorithms, or infrastructure, that decided whether a machine learning project succeeded or failed. Given this premise, Snorkel set out to explore the radical idea that you could bring mathematical and systems structure to the messy and often entirely manual process of training data creation and management, starting by empowering users to programmatically label, build, and manage training data.
In addition to the Factory founders of Chris Ré, Lip-Bu Tan, Ishan Mukherjee, Amarjit Gill and Andy Jacques, we are building a team of experienced operators who can drive execution in the startups we’re working with, as well as enabling the Factory’s Management Company and Fund to function at the highest level of governance and compliance. Our team includes -
Jessye Ball is currently the Factory COO. She has spent almost twenty years working for a range of financial services firms, evaluating investment opportunities both across asset classes and at the company level. Most recently she was part of the executive team within a Private Equity backed portfolio company, leading firm efforts surrounding operational growth strategy and efficiency. She earned her MBA from the Wharton School, University of Pennsylvania and BA from Boston College.
Deveaux Barron has over twenty years of organizational and business development expertise in advanced analytics and AI across financial services, insurance, and enterprise technology. She has worked in senior leadership positions at innovative companies such as Ayasdi, DataVisor, Finastra, and Deloitte. Deveaux focuses on building organizational success across business development, creating and scaling sales and distribution channels, and driving product strategy and client services. She is also aboard advisor to several startups as well as a board member of a number of nonprofits. In her current role as the Chief Revenue Officer at the Factory, she oversees business development and revenue generation strategy of the portfolio companies.
Krystal Suarez is a highly experienced administrative professional, who has played an integral role in the operational growth of venture funds and their portfolios. She is a versatile administrative manager, who is comfortable with high level executive support. Her experience has made her well versed in HR functions, full cycle recruiting, policy and procedure implementation, and growth strategy.
Nikesh Kotecha has worked in the healthcare space across a variety of environments and capacities and is leading the Factory’s MedTech and Biotech efforts. Most recently he started and led the informatics efforts at the Parker Institute for Cancer Immunotherapy. Prior to that he co-founded and built an analytics company around single cell proteomics and cytometry. His background and training include a PhD in Biomedical Informatics (Stanford) and a Bachelors in Bioengineering (Boston University). He stays involved in the community through various efforts working with community cancer clinics and as an adjunct professor at Stanford Immunology.
Sen Wu is a researcher at Stanford University and an EIR at the Factory. His interests span machine learning, data management, and machine learning systems. He received several awards including the SIGMOD Research Highlight Award, Communications of the ACM Research Highlight Award, and multiple ``Best of VLDB'' Awards. He received a Ph.D. in Computer Science from Stanford University, and B.E. in Computer Science from Tsinghua University.
The shift to data-centric AI is accelerating and the Factory’s companies will enable this, consequently capturing a huge amount of value in the process. Our unique investment approach allows founders to focus on leading the next evolution of AI, while we support and guide them operationally. In large part, this is made possible by you - the LP’s and Advisors who are equally part of the Factory. It’s incredibly exciting and we’re grateful to be on this journey with you all!
Please contact Andy Jacques at email@example.com with questions.