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Agnost AI

Agnost AI

AI

Product analytics for conversational agents that surfaces silent failures, user frustration and policy violations across every conversation.

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About Agnost AI

Agnost AI is a product-analytics layer for teams running conversational agents in production, built on the premise that a trace can report success while the user still got nothing useful. It reads every trace alongside the conversation it belongs to, maps it back to the user, and catches the failures traditional observability misses — the agent that claims it sent a PDF that never arrived, or that answers the wrong question confidently. Thousands of chats are auto-clustered into the recurring problems behind churn, ranked by how many users hit them, with every cluster linking straight to the exact conversations and traces. Alongside failures it surfaces what users are asking for and where they rage-prompt or give up, then hands back the highest-impact fixes with the evidence, a recommended change and the evals needed to ship it safely. Setup does not require rebuilding the agent: you install a skill, connect the events and conversations you already emit, inspect one staging trace, and turn it on.

Screenshots

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Key Features

Silent Failure Detection: Reads each trace next to the conversation to catch cases where the run reported success but the user got nothing useful, including broken promises and confidently wrong answers.
Automatic Conversation Clustering: Turns thousands of chats into ranked recurring problems, ordered by user impact and ready to investigate rather than left as raw logs.
Frustration and Churn Signals: Pinpoints where users rage-prompt, get stuck or abandon the conversation, so churn drivers are visible before the user leaves.
Policy and Quality Violation Alerts: Flags hallucinations and quality, policy and compliance breaches with the exact conversation and trace behind each one.
Evidence-Backed Fix Recommendations: Hands over the highest-impact fixes with supporting evidence, a recommended change and the evals needed to ship it safely.
Two-Step Skill Install: Connects to an existing agent by installing an agent skill and running one prompt, with no rebuild of the agent and no separate implementation project.
Feature Request Mining: Surfaces what users repeatedly ask for across conversations, turning support volume into a prioritised roadmap signal.
Live Demo Without Signup: Ships a public interactive demo where you can click any insight and inspect the underlying conversations before creating an account.

Use Cases

Diagnosing Agent Churn: Finding the recurring conversation pattern that makes users abandon a support agent, with the specific chats as evidence.
Auditing Production Agents for Compliance: Reviewing conversations for policy violations and unsupported claims across real traffic rather than a hand-picked sample.
Prioritising Agent Improvements: Deciding which prompt or flow to fix next based on how many users hit each failure cluster instead of on anecdote.
Catching Regressions After a Prompt Change: Watching whether a newly shipped change increases silent failures or user frustration in live conversations.
Building Evals from Real Failures: Turning observed production failures into regression evals so the same bug does not ship twice.
Mining Conversations for Roadmap Input: Extracting repeated feature requests from support and sales chats to feed product planning.

Frequently asked questions about Agnost AI

What is Agnost AI?

Product analytics for conversational agents that surfaces silent failures, user frustration and policy violations across every conversation.

How does Agnost AI work?

Agnost AI works by combining Silent Failure Detection: Reads each trace next to the conversation to catch cases where the run reported success but the user got nothing useful, including broken promises and confidently wrong answers., Automatic Conversation Clustering: Turns thousands of chats into ranked recurring problems, ordered by user impact and ready to investigate rather than left as raw logs., Frustration and Churn Signals: Pinpoints where users rage-prompt, get stuck or abandon the conversation, so churn drivers are visible before the user leaves., Policy and Quality Violation Alerts: Flags hallucinations and quality, policy and compliance breaches with the exact conversation and trace behind each one., Evidence-Backed Fix Recommendations: Hands over the highest-impact fixes with supporting evidence, a recommended change and the evals needed to ship it safely. to help users with Diagnosing Agent Churn: Finding the recurring conversation pattern that makes users abandon a support agent, with the specific chats as evidence., Auditing Production Agents for Compliance: Reviewing conversations for policy violations and unsupported claims across real traffic rather than a hand-picked sample., Prioritising Agent Improvements: Deciding which prompt or flow to fix next based on how many users hit each failure cluster instead of on anecdote., Catching Regressions After a Prompt Change: Watching whether a newly shipped change increases silent failures or user frustration in live conversations., Building Evals from Real Failures: Turning observed production failures into regression evals so the same bug does not ship twice..

What are the main features of Agnost AI?

Key features include Silent Failure Detection: Reads each trace next to the conversation to catch cases where the run reported success but the user got nothing useful, including broken promises and confidently wrong answers., Automatic Conversation Clustering: Turns thousands of chats into ranked recurring problems, ordered by user impact and ready to investigate rather than left as raw logs., Frustration and Churn Signals: Pinpoints where users rage-prompt, get stuck or abandon the conversation, so churn drivers are visible before the user leaves., Policy and Quality Violation Alerts: Flags hallucinations and quality, policy and compliance breaches with the exact conversation and trace behind each one., Evidence-Backed Fix Recommendations: Hands over the highest-impact fixes with supporting evidence, a recommended change and the evals needed to ship it safely..

Who is Agnost AI for?

Agnost AI is useful for anyone interested in Diagnosing Agent Churn: Finding the recurring conversation pattern that makes users abandon a support agent, with the specific chats as evidence., Auditing Production Agents for Compliance: Reviewing conversations for policy violations and unsupported claims across real traffic rather than a hand-picked sample., Prioritising Agent Improvements: Deciding which prompt or flow to fix next based on how many users hit each failure cluster instead of on anecdote., Catching Regressions After a Prompt Change: Watching whether a newly shipped change increases silent failures or user frustration in live conversations., Building Evals from Real Failures: Turning observed production failures into regression evals so the same bug does not ship twice..

How much does Agnost AI cost?

Agnost AI offers a free tier with paid plans for advanced features.

How do I get started with Agnost AI?

Visit https://agnost.ai/ to sign up and explore Agnost AI.

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