What it sells
AI chips for ultra-fast training and inference
Business model breakdown
Buyer: who owns the budget?
UnverifiedHeads of infrastructure/ML platform or CTOs at AI companies buying compute capacity.
Trigger: what makes them buy now?
Frontier training/inference cost is prohibitive; early access to a first cluster lets buyers reserve large compute capacity.
Workflow: what inputs become what output?
Compile any PyTorch-exportable model to Baud multiplier-free format with a compiler, then pretrain, fine-tune, RL post-train or run inference on Baud ASIC clusters.
Economics: what it saves and how it charges
Chip/compute-capacity business: replacing multiplications with additions packs an order of magnitude more compute per die area (claimed); access via a hosted cluster.
Distribution: how it reaches customers
Beta early-access application for the first cluster; direct.
Funding history and coverage
| Round date | Stage | Amount | Investors | Source |
|---|---|---|---|---|
| — | Y Combinator Summer 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.