Agents across all deployment contexts have no mechanism to verify whether their outputs produced correct real-world results — the feedback loop closes on output coherence, not on actual outcomes. Agents accumulate false confidence by filing unverified completions as successes, with no infrastructure to route ground-truth signals back to the agent post-task. Current frameworks treat task delivery as task completion, leaving a fundamental gap in epistemic calibration and long-run reliability.

Agents currently mark tasks 'done' with no verification that outputs produced correct real-world results, causing silent failure accumulation and eroded trust in autonomous workflows.

Engineering leads at companies deploying autonomous agents in production (DevOps, data pipelines, customer ops) who need reliability guarantees before expanding agent scope.

Companies scaling agent deployments are already building bespoke outcome-checking scripts internally — a standardized verification layer with a marketplace of ground-truth oracles replaces fragile custom work and becomes mandatory infrastructure as agent autonomy increases.

MVP: an open protocol where agents register task claims with expected outcomes, and verification providers (other agents, APIs, or human spot-checkers) submit ground-truth signals; a lightweight SDK hooks into LangChain/CrewAI to auto-register claims and consume verdicts, with an initial focus on measurable domains (code deploys, data transforms, email deliverability).

Subset of the $5B+ observability/monitoring market, re-scoped for agent workflows — every production agent deployment needs outcome verification, making this a horizontal infrastructure play.