The training platform for specialized agents
Turn your agents’ production data into specialized models you own. Prepare data, train, evaluate, and deploy from one platform.
From production data to a model you own
An AI lab for your engineering team.
You don’t need a frontier model for every task. Train smaller models for the work your agents do, from labeling emails to calling APIs, and measure them against the model you use today.
01 / Code and production context
Find the cause of agent failures.
Connect your repository and production traces to see how your agent makes decisions. Inspect the failing step, the tool call, and the context behind it.
02 / Data preparation
Turn real work into training data.
Build datasets from your agents’ production traces. Clean, filter, and prepare examples for training and evaluation, capturing the knowledge specific to your business.
03 / Evaluation and optimization
Prove improvements before you ship.
Test prompts and models against real tasks from your production data. Compare results with your current model, inspect failures, and catch regressions before deployment.
04 / Training and deployment
Train a model for your tasks.
Fine-tune an open model on your own data. Overmind handles training and deployment. You own the weights, with the choice to host on Overmind or run it yourself.
Intelligence-grade foundations
Built by AI & defense intelligence pioneers
Overmind is engineered on secure, robust foundations, not fragile wrappers. Founded by security engineers with combined decades of experience across defense intelligence, ML infrastructure, and fintech hyper-scaling.
Air-gapped & on-prem deployment
Run the entire harness inside your private cloud or local environment.
Zero third-party training
Your proprietary operational data never leaves your pipeline to train public foundation models.
Deterministic validation
Advanced verification harnesses ensure model outputs are empirically tested before deployment.
Common questions
What is Overmind?
Overmind is the training platform for specialized agents. It turns your agents' production data into specialized open-weight models you own. You prepare data, train, evaluate, and deploy from one platform.
How does Overmind turn production traces into a model I own?
Connect your agent with the Python SDK or send traces over OpenTelemetry. Your coding agent maps your agent's prompts, tools, and control flow, and Overmind generates evals from that map. The Data Workshop turns production traces into training data and checks it against your agent's contract.
You can then fine-tune an open-weight model, compare it with your current model on the same eval set, and serve it through an OpenAI-compatible API. You can also download the weights and run them yourself.
Do I need to rewrite my agent to start?
No. Set up the Python SDK once and it traces OpenAI, Anthropic, Gemini, Agno, and LangChain calls over OpenTelemetry. Mark each agent run with one call, and add decorators where you want more detail. There are no wrapper classes and no proprietary trace format.
Can I keep LangSmith (or another tracer) and still use Overmind?
Yes. Keep your existing tracer and use Overmind for datasets, training, benchmarking, and serving. Overmind also has its own tracing and evals.
You can import traces from Langfuse, LangSmith, Braintrust, and Galileo, or send them from any OpenTelemetry exporter over OTLP/HTTP.
Do I need my own ML infrastructure to train and serve?
No. Overmind recommends training settings from your dataset and runs LoRA or, where the model supports it, full fine-tuning on managed infrastructure. You can follow training metrics live and compare the result with your current model on the same eval set.
Serve the result on an Overmind endpoint through an OpenAI-compatible API, or download the weights and serve them yourself. Overmind also gives your coding agent a prompt that switches your app to the new model.
Own the model your product runs on
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