Technical or domain depth
Founders who know something about their problem that the market hasn't priced yet.
Early-stage AI
Supra is an early-stage firm investing at pre-seed and seed in AI infrastructure, tooling, agents, and vertical applications. We write early checks and move at the speed the round demands.
Thesis
We follow a layered reading of the AI stack. We study the whole value chain, then concentrate in the software layers where we have built, shipped, and hired — layers two through six.
Silicon and hardware we watch rather than underwrite: longer cycles, heavier capital, richer early pricing.
The question we ask
What breaks if a foundation model ships this natively? If nothing does, we keep listening.
Founders
Founders who know something about their problem that the market hasn't priced yet.
Something hard to copy — data, workflow depth, distribution, or genuine engineering difficulty.
Categories being redrawn by AI rather than incrementally improved by it.
No warm intro required. A short note about what you’re building is enough.
Send us a noteTeam
Fifteen years shipping AI and data platforms inside the companies that built this category, and a decade adjacent to the funds and labs where the next ones start.
Salesforce
Tech lead on the Einstein AI platform, search infrastructure, and analytics.
Ava Labs
Engineering leader on data and API platforms at protocol scale.
Matterport
Staff engineer and senior manager through the IPO.
Amazon
Infrastructure at consumer scale.
SoftBank
Technical advisor on due diligence across enterprise SaaS, data, AI, edge, and robotics.
Founded and exited
Built and sold an AI company for knowledge work in legal, healthcare, and voice.
VC Lab · Pi Ventures
Venture fellowships, one with a sub-10% acceptance rate.
Angel investing
Personal checks across frontier models, compute, and AI applications.
USC Viterbi
Instructor on AI agents and copilots.
Published research
arXiv papers on quantum-inspired and equivariant machine learning, plus 55+ articles on AI systems.
Six US patents
System architecture and cloud infrastructure, commercially licensed.
CMU · Stanford · Draper
Mentor and advisor at the Swartz Center, the Stanford Web3 and AI Research Group, and DraperU, where much of our deal flow starts.
Questions
Supra invests at pre-seed and seed. We write early checks and move at the speed the round demands.
The software layers of the AI stack: infrastructure and inference, models and model tooling, data, retrieval and developer tooling, agents, orchestration and workflow, and applications and vertical AI. We watch compute and hardware rather than underwrite them.
No. A short note about what you are building is enough. Every note sent through the site is read and answered either way.
Typically two weeks from the first call, and a clear no if it is a no. The first conversation usually happens within a week of reaching out.
Technical or domain depth, a defensible wedge that is hard to copy, and a market being redrawn by AI rather than incrementally improved by it.
The San Francisco Bay Area. Supra can be reached at [email protected].
Contact
Tell us what you're building, who it's for, and what you've learned that others haven't. We read everything that comes through here and reply either way.