Agent analytics

AI agents fail silently. Detect failures and fix them fast.

Silent failures become the most common way agents fail as they get better, and nothing in your monitoring catches them.

The problem

You find out when a customer complains.

By then an engineer has spent hours in the logs, only to find the same failure across hundreds of conversations, running for weeks. The tools you have weren't built to catch it.

Observability

One trace at a time

Great for debugging a single trace. Turning 50,000 of them into a trend takes days.

Evals

Only what you expected

They catch the failures you thought of. The costly ones are the failures you didn't.

Root cause

Nobody can tell you why

Ask an LLM which step caused a failure and it's right about 14% of the time.

Success metrics

Green is not correct

Returns 200, finishes, still wrong. A benchmark's success score was off by half until someone read the logs.

The shift

Stop treating agent quality as a feeling. Start treating it as a metric.