What it sells
Enterprise post-training, monitoring, and continual learning platform
Business model breakdown
Buyer: who owns the budget?
UnverifiedHead of Engineering / CEO at AI startups; research leads; enterprise AI leaders without an ML team.
Trigger: what makes them buy now?
Need a custom model on own data (data cannot leave the account, or agent performance on specific tool sets/workflows is insufficient) without hiring a research team.
Workflow: what inputs become what output?
Agents run: data curation (traces, docs, logs to training set), training (fine-tune to RL within a spend cap), evaluation in customer environment, serving (download weights or OpenAI/Anthropic-compatible endpoint).
Economics: what it saves and how it charges
Usage-based training/serving with customer-set spend caps; customer owns the weights. Claimed result: custom model tripled browser agent performance on EHR workflows at 20+ clinics (Novoflow).
Distribution: how it reaches customers
Demo-led: Book a demo CTA; docs and SDK available for Evals.
Funding history and coverage
| Round date | Stage | Amount | Investors | Source |
|---|---|---|---|---|
| — | Y Combinator Winter 2026 | — | 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.