What it sells
Distributed runtime for AI workloads at scale
Business model breakdown
Buyer: who owns the budget?
UnverifiedQuant, AI and data teams running large parallel compute (backtesting, RL, inference).
Workflow: what inputs become what output?
Run massively parallel workloads on clusters of 100-50,000 CPU/GPU nodes across hyperscalers and neoclouds using spot instances; <50 ms scheduling.
Economics: what it saves and how it charges
UnverifiedResells optimized compute; value is cheapest CPUs/GPUs across providers with Ray-based scheduler.
Distribution: how it reaches customers
Founder-led: Schedule a Call.
Funding history and coverage
| Round date | Stage | Amount | Investors | Source |
|---|---|---|---|---|
| — | Y Combinator Spring 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.