What it sells
Unlock wasted GPU capacity.
Business model breakdown
Buyer: who owns the budget?
UnverifiedHead of infrastructure / HPC / ML platform.
Trigger: what makes them buy now?
GPU jobs sized by guesswork cause out-of-memory failures and wasted capacity.
Workflow: what inputs become what output?
Install via Ansible/Helm on existing cluster; Analyse predicts runtime, memory, GPUs and failure risk before queue; Diagnose explains after run; loop improves predictions; serving fleets multiplexed automatically.
Economics: what it saves and how it charges
Value claim: more real work from same GPUs; example job 16xH100 11% completion to 97% with 45 min runtime; pricing model not stated.
Distribution: how it reaches customers
Book a discovery call (sales-led).
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.