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Enterprise Layer Intelligence
Categories/AI Orchestration & MLOps/Agnost AI
Agnost AI

Agnost AI

Monitor AI agents in production to catch silent failures and apply prompt fixes

Pricing model

Free Tier

Rating

★ People love it

Time to value

Quick Setup (< 1 hour)

You can use Agnost AI to monitor autonomous AI agents in production and identify recurring failures before users give up. It tracks conversations and nested tool calls alongside execution traces to uncover where users get stuck, re-prompt, or express frustration. The system automatically clusters similar failure patterns across conversations, highlighting total customer impact and affected message counts. From there, you can inspect trace details, test regression replays against past conversations, and approve generated prompt updates to fix agent behavior directly.

What Agnost AI does

Track conversation traces across live production AI agentsIdentify silent agent errors and unhelpful responsesGroup similar conversational failures into prioritized clustersReceive instant Slack notifications about rising agent issuesInspect message history alongside nested tool execution logsRun automated regression tests on suggested prompt revisionsApprove and apply prompt fixes directly from trace reviewsDetects silent failures when agents provide unhelpful or inaccurate responsesFlags user frustration, repeated corrections, and abandonment automaticallyClusters similar conversation failures to calculate total affected usersInspects nested tool calls and execution traces side-by-side with chatsDelivers automated Slack alerts for emerging failure patternsGenerates prompt changes and tests them with regression evaluationsEnables one-click approval to apply verified prompt fixes directly

Pricing breakdown

Pricing model: Free tier, Paid

PlanList price
FreeFree
Starter$49 / mo
Pro$499 / mo

Tutorials & Demos

Frequently asked

LangChainLangChainLangGraphLangGraphCrewAICrewAIMastraMastraOpenAIOpenAIAnthropicAnthropicAgnoAgnoDSPyDSPySlackSlack

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Agnost AI, AI agent monitoring, agent observability, silent failure detection, trace analysis, prompt debugging, LangGraph, OpenAI Agents SDK, CrewAI, regression evaluation, user frustration detection, LLM tracing