What it sells
GPUs for Agents
Business model breakdown
Buyer: who owns the budget?
UnverifiedML engineers, researchers and AI startup teams spending their own GPU budget (CTO or head of ML for larger teams).
Trigger: what makes them buy now?
GPU cost eating runway, or need for many parallel RL/eval sandboxes for agents.
Workflow: what inputs become what output?
Create a GPU instance from CLI or agent (tnr create), SSH in, snapshot disk when done; or fan out parallel sandbox rollouts from Python for RL environments, evals and post-training.
Economics: what it saves and how it charges
Usage-based GPU cloud billed per minute (instances) or per second (sandboxes), positioned as cheaper than AWS, Azure, GCP and CoreWeave (H100 $3.20 vs $6.16-$10.98 list).
Distribution: how it reaches customers
Self-serve signup with CLI, VS Code extension, API and MCP server; sandbox access by request; reserved capacity via contact; student and referral programs.
Funding history and coverage
| Round date | Stage | Amount | Investors | Source |
|---|---|---|---|---|
| — | Y Combinator Summer 2024 | — | 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.