What it sells
Infrastructure for AI labs to focus on research.
Business model breakdown
Buyer: who owns the budget?
UnverifiedResearch/infrastructure leads at AI labs; ML/AI leaders at enterprises.
Trigger: what makes them buy now?
Fragmented compute and failures eat research time; enterprises want a model that knows their private data.
Workflow: what inputs become what output?
Enterprise: scope the model and data, embed post-training researchers, train and iterate on Model Foundry, deploy to your cloud/ours/on-device, then hand off or keep updated (about 6 weeks to production).
Economics: what it saves and how it charges
Outcome-based: Model Foundry savings-share pricing, paying a share of what is saved on the compute bill; claims 3x more runs on the same budget and a specialist model at about a fifth of frontier cost.
Distribution: how it reaches customers
Sales-led: Plan a training run / Talk to an engineer.
Funding history and coverage
| Round date | Stage | Amount | Investors | Source |
|---|---|---|---|---|
| — | Y Combinator Fall 2025 | — | Y Combinator | ycombinator.com |
Profiles summarize public reporting and company websites. Business-model notes are MaxBC's reading of that material, not confirmed facts; unknowns are left blank rather than guessed. Updated 2026-10-12.