overmind-core/overmind

What it solves

Overmind addresses the challenge of continuously improving specialized AI agents by turning production data into actionable training and optimization workflows. It eliminates the need to build custom machine learning infrastructure by providing a unified platform to observe, evaluate, and fine-tune agents based on real-world performance traces.

How it works

You install the Overmind SDK and CLI into your agent's codebase. The platform instruments your agent to capture production traces, which are then stored as versioned datasets. You define evaluation metrics for your agent's capabilities, and Overmind uses these metrics to benchmark performance, run prompt or code optimizations, and perform fine-tuning. The platform integrates with popular IDEs via an MCP (Model Context Protocol) server, allowing you to trigger these workflows directly from your chat interface.

Who it’s for

This project is for developers and AI engineers building production-grade AI agents who need a structured way to monitor performance, create high-quality training datasets from live traffic, and iterate on agent behavior through automated evaluation and fine-tuning.

Highlights

• Production-Driven Training: Automatically converts production traces into fine-tuning datasets.
• Integrated Observability: Tracks agent capabilities, prompts, and tools using OpenTelemetry.
• IDE Integration: Connects to Cursor, Claude Code, and other MCP-compatible tools to manage agent workflows via chat.
• Self-Hostable: The entire platform can be self-hosted via Docker to keep data within your own network.
• Unified API: Serves both fine-tuned and frontier models through a single OpenAI-compatible API.