Built by engineers who shipagents to production.
Halios exists because we got tired of the gap between “it works in the demo” and “it's reliable in production.” We built the evaluation infrastructure we wished existed, and now we help other teams close the same gap.
Why we built this
We've been on both sides of the handoff problem.
We've spent years deploying AI systems for organizations where failure isn't acceptable. Every time, the same pattern emerged: the agent looked great in testing, but nobody could quantify whether it was ready for production.
We kept asking the same question, “how do we know this actually works?”, and kept getting the same answer: “we tested it manually.” That was not good enough.
So we built the evaluation engine we wished existed. One that captures real agent behavior in production, grades it against structured rubrics, and feeds the findings back into the development workflow. Evidence, not instinct.
Our Approach
Three principles shape every product decision.
Evidence over instinct
Every claim about agent quality should be backed by evaluation data, not manual spot-checks.
Closed-loop improvement
Evaluation is not useful if it stops at a score. The loop closes when findings feed back into the agent.
VPC-native by default
Your data should never leave your environment for the purpose of evaluating it. Full stop.
The team
A small, focused team based in San Francisco.
We've shipped production AI systems across customer support, enterprise automation, and conversational interfaces, and built Halios because the evaluation tooling we needed did not exist.
Menlo Park, CA
A small, focused team close to customers, shipping problems, and the reality of production AI.
What we build for
Teams that need evidence before they ship, not another demo environment that hides the hard parts.
Contact
We're here to help you ship reliable agents.
Let's talk about your agents.