Agnost AI

Agnost AI is a production analytics layer for teams shipping conversational agents. Instead of scoring an agent against a fixed test set, it continuously reads the real conversations, MCP tool calls and OpenTelemetry traces coming out of production, clusters them into recurring patterns, and ranks those patterns by how many users they hit.

The premise is that request-level observability is blind to the failures that matter most. A trace can report 200 OK, a tool call can succeed, and a response can be generated — while the user still got the wrong answer, or was told a document had been sent that never arrived. Those failures are only visible if somebody reads the conversation, and no team reads every conversation.

What it surfaces

• Silent failures — confidently wrong answers, hallucinated confirmations and broken promises, each linked to the exact conversation and trace behind it.
• Frustration and churn signals — the points where users rage-prompt, loop, or abandon the session.
• Unasked-for feature requests — recurring asks buried in chat logs, clustered so the volume behind each one is visible.
• Quality, policy and compliance violations, with the offending exchange attached.
• Recommended fixes delivered alongside the evidence and a suggested eval, so a discovered failure becomes a regression test rather than a one-off patch.

Getting connected

Instrumentation is roughly three lines of code, or an existing OpenTelemetry pipeline pointed at Agnost. The vendor also ships an installable agent skill (npx skills add AgnostAI/skills --skill agnost-ai) so a coding agent can wire up the integration itself. A live demo is browsable without signing up.

Pricing

Free up to 1,000 events per month with 7-day retention; Starter at $49/month for 10,000 events and 30-day retention; Pro at $499/month for 1,000,000 events and 90-day retention. Enterprise adds self-hosted VPC deployment, audit logs and custom SLAs. Agnost AI is a Y Combinator-backed company and reports processing over a million messages a day.