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Agent Compass is an intelligent error analysis system that points AI agent development teams in the right direction. It is capable of automatically identifying issues, group similar ones, learning from mistakes, and providing actionable guidance. Developers can leverage this system to course-correct by identifying what’s going wrong and how to fix it. Agent compass overview

What does agent compass do?

  • Error Detection & Direction: Automatically identifies and categorizes errors in agent execution, points out possible root causes and immediate fixes
  • Learning-Based Recommendations: Uses episodic memory from past agent runs and semantic memory from error patterns to recommend better solutions in future
  • Comprehensive Issue Tracking: Stores analysis results, error patterns, and improvement insights to track development progress over time
  • Pattern-Based Guidance: Automatically detects recurring problems in agent behavior and provides confidence-scored recommendations for resolution
  • Development Intelligence: Delivers detailed statistics and real-time insights that helps you understand where your agents are failing and how to improve

Supported Integrations

The following integrations are currently supported

LLM Models

OpenAI

OpenAI Agents SDK

Vertex AI (Gemini)

AWS Bedrock

Mistral AI

Anthropic

Groq

Together AI

Google ADK

Google GenAI

Portkey ADK

Orchestration Frameworks

LlamaIndex

LlamaIndex Workflows

Langchain

LangGraph

LiteLLM

CrewAI

Haystack

Autogen

PromptFlow

Vercel

Pipecat

Other

DSPY

Guardrails AI

Hugging Face smolagents

Ollama

Instructor

MCP

Configuring agent compass

You need absolutely zero configuration for using Agent Compass in your observe projects. Once you start sending traces to FutureAGI, the compass picks traces according to the sampling rate and generates meaningful insights The next section exhibits a walkthrough on setting up an observe project using the Google ADK integration to get insights from Agent Compass