Agnost AI
Agnost AI provides a monitoring and self-improvement platform for AI agents running in production. The platform automatically detects failures, runs diagnostic experiments, and opens pull requests with fixes, integrating with coding agents like Claude, Codex, and Cursor via a single command. It offers observability across major agent frameworks including CrewAI, LangGraph, LangChain, and OpenAI Agents SDK.
- Artificial Intelligence
- Developer Tools
- AI Agents
- Data & Analytics
- Software Only
Funding
Raised to date
$500KRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Founder details are not available yet.
Product
Problem
AI agents deployed in production frequently fail silently—through tool errors, poor reasoning, or misaligned outputs—without teams having clear visibility into what went wrong. Debugging and improving agents requires manually sifting through traces, guessing at root causes, and deploying fixes, which is slow and error-prone. This lack of automated feedback loops prevents agents from reliably improving over time.
Solution
Agnost AI offers a monitoring and self-improvement platform that watches AI agents in production. It automatically detects failures, runs diagnostic experiments, and opens a pull request with a fix—continually. The platform integrates with coding agents like Claude, Codex, and Cursor through a skill installed via a single command, making setup simple. It provides agent observability across frameworks such as CrewAI, LangGraph, LangChain, and OpenAI Agents SDK, enabling teams to trace tool calls, latency, and outcomes. By distinguishing execution success from actual user outcomes, Agnost surfaces silent failures and drives an improvement loop from production conversation data to shipped fixes.
Target Audience
Primary customers are AI engineering and product teams running agents in production who need observability and automated improvement loops, as well as teams using major agent frameworks like LangChain, CrewAI, and OpenAI Agents SDK.
Features
- Automatic failure detection and experiment-driven PR generation to fix agent issues without manual intervention
- Skill-based integration with Claude, Codex, and Cursor via `npx skills add AgnostAI/skills --skill agnost-ai`
- Framework-specific observability guides and instrumentation for CrewAI, LangGraph, LangChain, OpenAI Agents SDK, Pydantic AI, DSPy, Mastra, Vercel AI SDK, and others
- Product analytics dashboard focused on intent, trust, friction, handoff, recovery, and improvement loop metrics, not just system health
- OpenTelemetry-based trace capture preserving conversation identity, with separation of first-token latency, completion, tool execution, and user outcomes