What is Kelet

Kelet is an observability and automated debugging platform designed specifically for production-grade LLM applications and AI agents. Unlike traditional monitoring tools that simply display dashboards, Kelet acts as an autonomous detective that ingests your traces and signals to identify, classify, and resolve failure patterns. By analyzing thousands of sessions, it surfaces the root cause of failures and provides actionable prompt patches. The platform streamlines the feedback loop by allowing engineers to test fixes against real historical sessions, ensuring reliability before deployment. With support for major frameworks like LangChain, CrewAI, and the AI SDK, Kelet reduces the time spent manually scrolling through logs, helping teams reclaim engineering hours and maintain high-performing AI agents.

Kelet 's Core features

Automated Root Cause Analysis

Automatically identifies why an agent failed by analyzing traces, eliminating the need for manual log inspection.

Failure Pattern Classification

Clusters thousands of sessions to group similar errors, helping teams prioritize the most impactful fixes.

Actionable Prompt Patching

Provides specific, evidence-backed prompt adjustments to resolve identified failure patterns immediately.

Reliability Verification

Runs proposed patches against real historical session data to prove the fix works before it goes live.

Broad Framework Support

Integrates seamlessly with LangChain, CrewAI, Pydantic, Agno, and other popular AI development stacks.

Continuous Learning Loop

Ensures every production mistake becomes a lesson, constantly refining agent performance over time.

How to use Kelet

Connect your AI agent stack by integrating Kelet with your existing observability tools or SDKs.,Allow Kelet to ingest production traces, signals, and user feedback automatically.,Monitor the dashboard to identify failure patterns classified by the system.,Review the AI-generated root cause analysis and evidence for each identified issue.,Apply the suggested prompt patch and verify the fix using Kelet’s before/after reliability measurements.,Deploy the validated fix to production with confidence.

Use cases of Kelet

Reducing Debugging Time

Drastically cuts down the 30% of engineering time typically spent manually guessing fixes for agent failures.

Production Reliability Engineering

Ensures AI agents remain stable in live environments by catching silent failures that standard dashboards miss.

Prompt Engineering Optimization

Uses real-world failure data to iterate on and improve system prompts with empirical evidence.

Who benefits from Kelet

AI Engineers

Developers building and maintaining complex LLM applications who need to minimize downtime.

MLOps Teams

Teams responsible for the deployment, monitoring, and reliability of production AI agents.

Product Engineering Leads

Managers looking to improve developer velocity by automating the tedious process of debugging AI agents.

Kelet