# The model training platform for AI teams

Overmind turns your production traces into specialised models you own, automatically trained, benchmarked, and served.

The AI engineering copilot for agent optimisation and model training.

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Overmind is the model training platform for AI teams. Turn your production traces into specialised models you own, trained, benchmarked, and served.

## See everything your agents do

Get a granular view of your agents. Overmind builds a context graph: code, prompts, tools, and runtime behaviour.

### The agent context graph

Your biggest edge is knowing your agent completely. Overmind maps your whole agent into one graph: every prompt, tool, decision path, and dependency, discovered from the codebase and kept honest by traces from a single SDK setup. Evals, datasets, optimisation, and training all draw from that one shared picture.

## Turn real behaviour into datasets

Your agents already generate the data. Overmind lifts your best production runs into audited training and eval sets, checked against your agent and ready to train on.

### Dataset curation from production traces

Your agent's best production runs become training and eval data. Every example is validated and checked for fit against the agent it came from, with full provenance back to the trace it started as.

### Data pre-processing in the Workshop

Clean data multiplies everything you train on it. The Workshop audits every dataset twice: deterministic checks catch duplicates, broken structure, and PII in seconds, then a coding agent reads the corpus for the problems rules miss. Every proposed fix is verified before you see it, and applying one is a click.

## Catch regressions before your users do

Evals generated from your agent's own behaviour. Every change scored against your baseline. Fixes to improve performance generated as a PR.

### Evals generated from context

Get eval coverage without writing evals. The graph knows what each agent is designed to do and how it can fail, so scoring criteria are generated for exactly that. Every run reports per-metric scores you can track across models, prompts, and releases.

### Ship the winning change as a PR

The Optimiser rewrites prompts, tool definitions, and agent logic as real git diffs, each scored against your baseline on the same eval set. The winning change opens as a reviewable PR, and when tweaks stop paying off it tells you it is time to train.

## Own your intelligence

Train on your agent’s own data. Benchmark against the model you run today. Run inference on Overmind, no ML infra required.

### Automate model training

Training your own model takes a couple of clicks, because the hard decisions are already made by your data. Overmind recommends the model tier and hyperparameters, estimates cost and duration before you commit, and charts progress live. Deploy on Overmind's inference or your own stack.

## Own the model your product runs on

Create a free account and get started

- [Start for free](https://console.overmindlab.ai)
- Talk to the team: https://www.overmindlab.ai/contact