Runtime control for the AI era
From a belief that AI apps need local-first guardrails to a runtime layer used by teams shipping OpenAI at scale. We're building the control plane that sits inside your application, not in front of it.
Our vision
"AI infrastructure shouldn't just observe — it should enforce policy before a request ever reaches a provider."
Traditional AI governance was built for a different era — proxies, gateways, and external policy servers. We're creating the first true runtime-native control layer that evaluates, budgets, and traces inside your application.
By combining precise cost estimation with local policy enforcement, we've built a system that protects budget, blocks unsafe tool calls, and produces rich traces — all without adding infrastructure overhead or handing over provider keys.
Built by
Captar
We're building the runtime control layer for production AI. Small team, big ambitions.
The road so far
Captar founded
Started building local-first runtime guardrails for AI apps.
V1 traces and datasets
Shipped span-first tracing, budget guardrails, and dataset import.
Manual evals and beyond
Reviewer-driven evaluations, tool tracking, and production stability.
"We believe AI should be observable, controllable, and accountable — not a black box that ships to production without guardrails."