Find user frustration
Shows where an agent fails, where users get frustrated, and how those patterns relate to the exact conversations and traces behind them.
Agnost AI
Agnost AI is product analytics for conversational agents. It helps teams find silent failures, user frustration, feature requests, and policy violations across production conversations.
Product analytics for conversational agents
Agnost AI is a product analytics tool for conversational agents. It is built to help teams see what users are asking for, where they get frustrated, and where an agent fails silently even when traces or system checks look successful.
The product focuses on production conversations and links insights back to the exact conversation and trace so teams can investigate issues, prioritize fixes, and decide what to change in prompts, product flows, or evaluations. The site positions it as useful for catching silent failures, feature requests, and policy or quality violations across real traffic.
What Agnost AI does
Auto-cluster conversations
Groups large volumes of chats into recurring problems so teams can investigate what is happening most often and what is having the biggest impact.
Prevent costly failures
Surfaces hallucinations, broken promises, and policy violations with the supporting conversation and trace for each incident.
Fix what matters
Highlights the fixes with the most impact and includes evidence, a recommended change, and evals needed to ship safely.
Get started in minutes
Connects to existing agent events and conversations in a short setup flow, so teams can start reviewing real traffic without rebuilding their agent.
Where Agnost AI fits
Detect silent failures
Useful when an agent appears healthy in traces but users are still abandoning tasks, rage-prompting, or getting no useful outcome.
Analyze production conversations
Helps teams identify repeated complaints, feature requests, or confusing behavior across many chats instead of reading each conversation manually.
Review quality and compliance issues
Helps teams catch hallucinations, broken promises, and policy violations with evidence attached to the incident.
Prioritize improvements
Supports product and prompt work by showing which fixes are most important and what evidence supports a change.
Start from existing telemetry
Gives teams a way to review real traffic after a quick connection process, without rebuilding the agent from scratch.
Pros and Cons
Pros
- Connects analytics to both the conversation and the trace behind each insight.
- Designed to surface silent failures that can be missed by standard success metrics.
- Groups recurring issues so teams can prioritize by impact instead of reviewing chats one by one.
- Includes pricing with a free tier plus paid plans, which makes the product easy to try before committing.
- Provides guidance on next-step fixes rather than only reporting problems.
Cons
- The public pages do not provide a full integrations list or platform matrix.
- Security handling is partly manual: the site says users should redact secrets or sensitive fields before ingestion and does not claim automatic PII redaction.
FAQ
How is Agnost AI different from regular observability or traces?
Agnost AI says it reads conversations alongside traces so teams can catch cases where a trace looks successful but the user still did not get value. The product is positioned for situations where standard observability is not enough to explain user frustration or silent failure.
How does setup work?
The site says you can connect the events and conversations you already have, inspect one staging trace to confirm what is being sent, and then turn it on. It also mentions a two-step setup and an example skill install command, but it does not publish a full integration list on the pages provided.
Is there a free plan?
The pricing page lists a free plan and paid Starter, Pro, and Enterprise tiers. The free plan includes automatically discovered intents and sentiment, quality/policy/compliance violations, alerts for silent failures and rising friction, self-improvement suggestions, up to 1,000 events per month, and 7-day retention.
Is customer data secure?
The terms page says Agnost processes the conversation data you choose to send, recommends pseudonymous IDs and redacting secrets or sensitive fields before ingestion, uses HTTPS for transport, and authenticates dashboard access. It also notes that the company does not automatically redact PII for you.
Can the team help improve my agent?
The FAQ and terms indicate that the founders are available to help, and the site invites users to talk to the founders directly. The product is early-stage and positioned as a service where the team may help interpret insights and turn them into prompt, product-flow, or eval changes.
Quick Facts
- Category
- Product analytics for conversational agents
- Primary users
- Teams building or operating AI agents
- Source domain
- agnost.ai
- Pricing shape
- Free tier, paid starter/pro/professional tiers, and enterprise custom pricing
- Setup
- Connect existing events and conversations; site describes a two-step onboarding flow
- Notable workflow
- Review conversation and trace together, then prioritize fixes and evals
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