Why this exists
Monitoring catches crashes. Verification catches lies.
The industry shipped AI agents faster than the ability to check them. Uptime, latency,
error rates — the whole observability stack watches whether the run finished.
None of it watches whether the run did the job.
An agent that fails loudly is a solved problem. The dangerous one finishes on time,
writes fluent output, reports success — and quietly delivers nothing, or worse,
yesterday's world presented as today's. The more polished the output, the longer the
failure survives.
“A result that never reached its destination didn't happen — no matter
how good it looks in the logs.”
Carell.ai closes that gap with something your own tooling structurally can't provide:
an independent check. Self-review is how fabricated citations end up in published
reports. A verification layer that answers to the evidence — not to the team that built
the agent — is the difference between “it said it worked” and “it worked.”
We run it on our own agents every day. Our failures were the training data; our
deployment is the first customer.