What it sells
Ultra-low latency inference cloud for real-time workloads
Business model breakdown
Buyer: who owns the budget?
UnverifiedEngineering/infrastructure leads at AI-native companies running production agents (inferred from pitch about owning agent SLAs).
Trigger: what makes them buy now?
Latency spikes, errors, downtime and uncontrolled cost creep on shared black-box API providers as agents scale.
Workflow: what inputs become what output?
Replaces calling shared model APIs: deploy open-source/custom models on managed single-tenant inference clusters across clouds and 10+ regions with custom API SLAs.
Economics: what it saves and how it charges
Dedicated managed inference clusters sold with SLAs (claims 99.99% uptime for models, 99.999% cluster uptime); pitch is predictable costs at scale vs shared API cost creep. Exact billing model not published.
Distribution: how it reaches customers
Sales-led: "Contact sales" and "Talk to an engineer" CTAs (cal.com booking); technical blog deploy guides and infrastructure partnerships (Neysa, Armada).
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.