Watch an agent get validated while it's still running
Autonomous Validation is Oprimes' Validation & Reliability pillar in continuous form: automated scoring catches most of it in under 200ms, and what it can't judge on its own, a matched human reviewer picks up in minutes — so agents ship accurate, reliable, safe, and ready for the real world, not just passing on a pre-launch eval.
A 95% reliable step doesn't make a 95% reliable agent
This is what single-turn evaluation misses: the same small error rate, carried across every step of a real agent workflow, until the number that reaches production looks nothing like the number in the eval report.
One continuous pipeline, not a pre-launch checklist
Click a stage to see what happens there. This is the same path every run takes, whether it's the first test before launch or the ten-thousandth call in production.
Agent Run
Every step of every task is ingested automatically, connected via API or pulled from trace logs, from any agent framework including LangGraph, CrewAI, or a custom orchestration stack. Nothing needs to be manually exported for a run to enter the pipeline.
What actually gets caught, as it happens
A representative feed of the kind of findings that surface once an agent is under continuous validation, rather than checked once before launch.
Neither approach alone covers what Autonomous Validation covers
Automated scoring and human review each cover part of the problem. Autonomous Validation is built to combine both, so no dimension is left uncovered.
- 100% traffic coverage, <200ms per check
- Struggles with nuance: tone, ambiguity, cultural fit
- Runs continuously, 24/7, at production scale
- Score alone rarely satisfies an auditor
- Sampled coverage; most traffic goes unreviewed
- Strong on nuance, tone, and edge-case judgment
- Doesn't scale to every production call
- Produces a defensible, documented judgment
- 100% traffic coverage, <200ms automated pass
- Ambiguous cases escalate to a matched human reviewer
- Continuous, 24/7, on live production traffic
- Every finding mapped to a regulatory control, audit-ready
Single-response eval passes and multi-step agents still fail three turns into a real conversation. Autonomous Validation is built to catch that gap before a user does — scoring every step automatically, and routing anything ambiguous to a reviewer matched by language, region, and domain expertise.
Questions about Autonomous Validation
Most eval tools score a single response in isolation. Autonomous Validation scores the full multi-step agent workflow continuously, and escalates ambiguous or high-risk cases to human reviewers instead of leaving them as a silent scoring error.
Automated confidence falling below a set threshold, content touching a high-risk category like financial or medical advice, or a pattern the automated layer flags as ambiguous rather than clearly pass or fail.
Autonomous Validation is framework-agnostic, connecting via API or trace log upload, and has been used with LangGraph, CrewAI, and custom orchestration stacks.
Both. Pre-launch, it runs full workflow simulations and adversarial testing. Post-launch, the same automated-plus-human loop continues on live traffic, catching drift before it reaches scale.
Current mappings cover the EU AI Act, SR 11-7 model risk guidance, DORA, and NYDFS Part 500, with additional regional mappings added as engagements require.
No. Autonomous Validation applies to any multi-step AI agent, including support copilots and research assistants. Regulatory-mapped evidence is most commonly used by regulated enterprises in financial services and healthcare.
See your agent's real, multi-step reliability, not the number in the eval report.
Connect an agent or upload a trace log, and an Oprimes AI trust expert will walk you through your first Autonomous Validation run.
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Let the right humans validate it.
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