Maat checks every plan, handoff, and action as it happens — catching small failures before they spread, instead of after they reach production.
Chain agents together and a 95%-reliable step becomes a 60%-reliable workflow. One agent's malformed output silently becomes the next one's input — until it surfaces as a wrong decision delivered with confidence. Maat catches those failures between the steps.
Your agents see verdicts — pass, fix, or stop — never the rules that produced them. The methodology stays on your infrastructure.
Rejects an underspecified or broken plan before a single agent runs — no goal, no forecast, no owner, no go.
Inspects every handoff for missing, redundant, unverifiable, or contradictory data — and names the agent that produced it.
Light checks when the fleet is healthy; full scrutiny exactly when an agent is on probation or the stakes are high.
Scores each action for harm, dishonesty, and duty. Crosses a line, it refuses — cites the principle, demands alternatives, logs it.
Predicts an agent running out of resources, drifting out of sync, or losing its thread — and calls a human before it fails.
Watches the failure trend. When it climbs, the agent is paused and escalated — then earns its way back.
Your agents call the Maat API with a single request. Pick an endpoint to see the request — and the verdict it returns.
Keep your stack — LangGraph, CrewAI, or your own. Route each handoff through Maat and act on the verdict. The methodology never leaves the server.
Maat's gates are deterministic — microseconds per call, no model bill. So metering is honest and the floor is low.
Pricing shown is illustrative — final tiers set at launch.