We keep AI clusters healthy so your jobs don't pay for it.

KTLO AI Labs was started by infrastructure and reliability engineers who spent too many nights chasing GPU-hours lost to failures that never crashed loudly — a node quietly throttling, a fabric link slowly degrading, a page with no context at 3 a.m. We're building the platform, and the operational backbone, we always wished we had.

Our mission

GPU fleets are expensive, dense, and unforgiving — and the tooling to keep them healthy is fragmented across vendors and stitched together with CLI one-liners and tribal runbooks. Our mission is to give every AI cluster operator a single, trustworthy way to detect degradation, understand it, and fix it — across compute, the fabric, and storage, and across the hardware they run today and the hardware they'll run next.

We're building cloud-native, AI-native tooling on top of the open source health monitoring stacks the industry already trusts — not replacing them, but giving them a brain. And most importantly: we don't stop at detection. Intelligent software takes the first pass at the fix, and only calls in a human when it genuinely needs one — so impact stays small and your team isn't paged for things a machine could have handled.

Founding team

KTLO AI Labs is founded by two engineers who managed AI cluster health and uptime for years inside a large AI cloud provider — not as an occasional project, but as the job, every day: diagnosing failing nodes, tuning alert thresholds, and standing up the remediation automation that kept massive GPU fleets earning their keep. We're building the platform we wish we'd had.

What we believe