Silent-failure detection
Flags signals such as user corrections, repeated questions, frustration, and abandonment so teams can investigate problems without waiting for a formal bug report.
Agnost AI
Freemium
Agnost AI monitors AI agents in production by analyzing conversations, traces, user corrections, and frustration. It helps teams identify recurring failures, review suggested prompt fixes, and apply approved changes with replay-based regression coverage.
What is Agnost AI?
Agnost AI is a production monitoring tool for AI agents. It analyzes agent conversations and captured operations to surface silent failures that may not generate conventional bug reports, including users correcting the agent, repeating requests, becoming frustrated, or abandoning a conversation. The product is intended to help teams understand where an agent is failing in real usage and which problems affect the most users.
The workflow moves from recurring problem discovery to remediation. Agnost groups similar conversations into intents or failure clusters, shows the messages behind a cluster, and lets users inspect an individual message together with its nested tool calls and traces. This provides context for determining whether the issue came from the agent’s response, a tool interaction, or another part of the execution.
For supported problems, Agnost can suggest a prompt change or other agent fix. Teams can review the proposed change, inspect replay results, and approve it before the fix is applied automatically. Generated regression cases can then cover the reported behavior and show whether the alert is resolved, helping teams keep a previously observed failure in view.
Agnost can be connected to agents built with frameworks and SDKs including LangChain/LangGraph, OpenAI Agents SDK, CrewAI, Vercel AI SDK, Pydantic AI, Mastra, OpenAI, Anthropic, Agno, DSPy, VoltAgent, and Spectrum-TS. The site also lists Python, TypeScript, and OpenTelemetry for teams building their own harness. Setup is presented as a two-step process using the Agnost AI skill.
Plans include a free tier with 1,000 events per month and seven days of data retention, a $49-per-month Starter plan with 10,000 events and 30 days of retention, a $499-per-month Pro plan with 1,000,000 events and 90 days of retention, and a custom Enterprise plan. Event usage is measured over a rolling 30-day window; when a limit is reached, automated analysis and dashboard access pause until usage falls below the allowance or the account is upgraded.
What can Agnost AI do?
Failure clustering
Groups similar conversations and reports how many users or traces are affected, helping teams compare recurring problems and prioritize growing clusters.
Conversation and trace inspection
Links flagged messages to their surrounding conversation and nested traces, including tool calls, so teams can follow a failure to the agent behavior that produced it.
Suggested fixes with approval
Produces suggested prompt changes or fixes that teams can review rather than applying automatically without a decision.
Replay and regression coverage
Shows replay results for a proposed fix and generates regression cases from observed traces so resolved alerts can be checked against the original behavior.
Production agent analytics
Provides automatic intent and sentiment discovery, detection of quality, policy, and compliance violations, and alerts for silent failures and rising friction.
Use Cases
“Investigating user corrections”
A support or product team can open a cluster of conversations where users corrected the agent, read the affected messages, and inspect the related trace to determine why the response was wrong.
“Prioritizing recurring agent issues”
An AI operations team can compare failure clusters by affected users and trace counts, then focus engineering attention on problems that are repeating or growing.
“Reviewing an agent improvement”
A developer can examine a suggested prompt change, check replay results against captured cases, and approve the fix once the evidence supports it.
“Monitoring agents across frameworks”
A team building an agent with a listed framework or SDK can connect its production activity through the available skill and inspect conversations, tool calls, and failures in one monitoring workflow.
Frequently Asked Questions
What does Agnost AI monitor?
It monitors production agent activity, including conversations, messages, traces, nested tool calls, and captured operations. Its analysis looks for intents, sentiment, user corrections, frustration, silent failures, and quality, policy, or compliance violations.
How is an event counted?
An event is one captured operation, such as an agent turn, model generation, or tool call. A single conversation can contain several events.
What happens when an event limit is reached?
Usage is measured over a rolling 30-day window. At the plan limit, automated analysis and dashboard access pause. Users can upgrade in Settings or wait until usage falls below the allowance.
Can suggested fixes be applied automatically?
A team reviews the suggested prompt change and replay results first. The fix is applied automatically only after an authorized user approves it in Agnost.
What are the available plans?
The site lists Free, Starter, Pro, and Enterprise plans. Free includes 1,000 events per month and seven days of retention; Starter is $49 per month with 10,000 events and 30 days; Pro is $499 per month with 1,000,000 events and 90 days; Enterprise uses custom limits and pricing.
Quick Facts
- Category
- AI agent monitoring
- Primary environment
- Production AI agents
- Core workflow
- Clusters → messages → traces → approved fix
- Setup
- Connect through the Agnost AI skill in two steps
- Listed integrations
- LangChain/LangGraph, OpenAI Agents SDK, CrewAI, Vercel AI SDK, Pydantic AI, Mastra, OpenAI, Anthropic, Agno, DSPy, VoltAgent, and Spectrum-TS
- Free plan
- 1,000 events per month with seven days of data retention
Agnost AI Traffic Analysis
Traffic data is for reference only.
- Domain Rating
- 38
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