AfterQuery is a San Francisco applied research lab that builds expert-generated datasets, benchmarks, and reinforcement-learning environments for the world's leading AI labs. The company recruits nearly 100,000 vetted domain experts - in finance, law, medicine, software, and beyond - to teach frontier models how specialists actually think.
Henry Ehrenberg is Co-Founder and Head of Engineering at Snorkel AI, the data-centric AI company he helped build out of Stanford's AI Lab in 2019. With a background in applied mathematics (Yale) and computational engineering (Stanford), Ehrenberg co-developed the Snorkel system — a paradigm-shifting framework for training machine learning models using programmatic weak supervision rather than hand-labeled data. Snorkel AI has raised $338M total, including a $100M Series D in May 2025 at a $1.3B valuation, and counts five of the top ten US banks, Fortune 500 companies, and leading research labs like Google, OpenAI, and Anthropic among its clients.
Jason Warner is the co-founder and CEO of Poolside, a San Francisco-based frontier AI lab building proprietary foundation models for software development with $626M raised and a $3B+ valuation. Before Poolside, he was CTO of GitHub - where he launched Actions, Packages, Codespaces, and incubated what became GitHub Copilot - and then a Managing Director at Redpoint Ventures. A self-described 'average developer but excellent architect,' Warner is betting that reinforcement learning from code execution will make software the first domain where AI surpasses human-level intelligence.
Poolside is a San Francisco AI lab building foundation models purpose-built for software engineering. Founded in 2023 by former GitHub CTO Jason Warner and serial entrepreneur Eiso Kant, it trains its frontier models (malibu, point) with a technique called Reinforcement Learning from Code Execution Feedback - then deploys the whole stack inside customer environments for Global 2000 enterprises, financial institutions and the public sector.
Wirestock is a two-sided marketplace that connects 700,000+ photographers, videographers, illustrators, and 3D artists with AI labs that need ethically-sourced, high-quality multimodal training data. After pivoting from stock-content distribution in 2023, the company now supplies six of the largest foundation-model makers and is running at a $40M revenue run rate.
Spencer Mateega is the 23-year-old Co-Founder and CEO of AfterQuery, a San Francisco-based applied research lab that captures expert professional knowledge and converts it into high-quality training data for AI foundation models. Founded in January 2025 and backed by Y Combinator's Winter 2025 cohort, AfterQuery raised a $30 million Series A at a $300 million valuation in April 2026, with revenues exceeding $100 million annualized. Mateega's philosophy — 'We teach machines how experts think' — drives a platform connecting roughly 100,000 domain professionals in finance, legal, and software to frontier AI labs hungry for reasoning-rich data.
Vipul Ved Prakash is a serial entrepreneur and technologist who co-founded Together AI, an AI acceleration cloud platform valued at $3.3 billion after a $305M Series B in February 2025. Previously, he built Topsy (acquired by Apple for $200M+), co-founded Cloudmark (acquired by Proofpoint), and created Vipul's Razor - one of the internet's first collaborative anti-spam systems. A self-described cypherpunk with a table-tennis past, Prakash has been dismantling bottlenecks - from spam to closed AI - for over two decades.
Profluent is an AI-first protein design company building frontier models that author novel proteins - including the first AI-designed CRISPR gene editor, OpenCRISPR-1. Based in Berkeley's biotech corridor, the company applies the same scaling-law playbook that worked for language models to the language of biology, then validates the outputs in a wet lab.
TwelveLabs is a San Francisco-based AI company building video-native multimodal foundation models that give machines the ability to see, hear, and understand video the way humans do. Its flagship models - Marengo for embedding and retrieval and Pegasus for video-to-text generation - power enterprise applications in media, government, sports, and security, enabling precise semantic search, summarization, and insight extraction from video at scale. With 30,000+ developers on its platform and backing from NVIDIA, Databricks, Snowflake, and In-Q-Tel, TwelveLabs is becoming the standard infrastructure layer for video intelligence.
Ron Alfa is Co-Founder and CEO of Noetik, an AI-native biotech building foundation models trained on one of the world's largest collections of multimodal human tumor data. A physician-scientist with an MD-PhD from Stanford and an MA in the History of Medicine from UCL, Alfa spent six years at Recursion Pharmaceuticals rising to SVP Head of Research before co-founding Noetik in 2023. The company's OCTO-VC virtual cell models and TARIO-2 autoregressive transformer are designed to predict which cancer patients will respond to which therapies - attacking the 95% failure rate of cancer clinical trials from the data side rather than the pharmacology side. In January 2026, Noetik signed a landmark $50M licensing deal with GSK, one of the first large-scale transactions to monetize a biological foundation model as a scalable enterprise asset.
Alexander Ratner is the co-founder and CEO of Snorkel AI, the company he spun out of Stanford's AI lab in 2019 after building the Snorkel open-source project during his PhD. A Harvard physics graduate turned Stanford computer scientist, Ratner pioneered the field of data-centric AI and weak supervision - the idea that better data, not just better models, is the key unlock for enterprise AI. Under his leadership, Snorkel AI reached a $1.3 billion valuation in 2025 following a $100 million Series D, with $148M in annual revenue and customers including some of the world's largest enterprises and LLM developers.
Chip Huyen is a Vietnamese-American computer scientist, author, and educator who turned a rejection letter from Stanford into a three-year around-the-world journey, two bestselling Vietnamese travel books, and eventually a second application that got her in. She went on to teach at Stanford, build ML infrastructure at NVIDIA and Netflix, co-found Claypot AI, and write two of the most-read technical books on machine learning systems in production - 'Designing Machine Learning Systems' (2022) and 'AI Engineering' (2025). Her newsletter and blog are required reading for anyone building serious AI products.
Dilawar Mahmood is a machine learning engineer at ZeroEntropy (YC W25) in San Francisco, best known for four years at Apple where he optimized on-device models for Siri and Spotlight - work he once presented directly to Tim Cook at the Steve Jobs Theater. A Norwegian-educated engineer who left a comfortable career track to attend the Recurse Center and rediscover what programming actually feels like, he builds distributed ML frameworks in his spare time and is on record hating vibe coding.