Overmind
Train, evaluate, and deploy specialized models using your agents’ production data while retaining ownership of the model weights.
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Product Overview
What is Overmind?
Overmind helps engineering teams turn agent production data into specialized models for their own tasks. It connects code and execution traces with dataset preparation, evaluation, fine-tuning, and deployment in one platform. Teams can compare trained models against their current models, retain ownership of the weights, and choose managed hosting or self-hosting.
Key Features
Agent Failure Analysis
Connect repositories and production traces to inspect agent decisions, failed steps, tool calls, and their surrounding context.
Training Data Preparation
Clean, filter, and organize production traces into datasets for model training and evaluation.
Model and Prompt Evaluation
Test models and prompts on production tasks, compare results with existing models, and identify regressions before deployment.
Specialized Model Training
Fine-tune open models on proprietary task data, with training and deployment managed through the platform.
Ownership and Hosting Control
Own your trained model weights, choose managed or independent hosting, and self-host the open-source platform with Docker Compose.
Use Cases
- Task-Specific Agent Models : Train smaller models for recurring agent tasks such as email labeling and API calling.
- Agent Debugging : Investigate failed agent runs by examining execution traces alongside repository context.
- Production Dataset Development : Convert real agent interactions into reusable training and evaluation datasets tailored to business workflows.
- Model Replacement Validation : Compare specialized models with current models on real tasks before deciding whether to switch.
FAQs
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