02PRODUCTS / ML HARNESS

Plan, sandbox, evaluate, and benchmark — locally.

A plug-in-place harness for machine learning work on your machine. It plans the run, builds sandboxes, generates and evaluates data, benchmarks results, and attaches the model you choose — so you get a full local ML loop without building the scaffolding yourself.

02.1STACK

ML Harness layers

Select a plane or legend row to inspect each layer.

·++·+···:·:·::Plan·:+··+:·:·+··+··+Sandbox++··+·:··+·::+·Data·++·+···:·:·::Eval·:+··+:·:·+··+··+Benchmark

02.2DEPTH

What ML Harness runs

Boxes in the loop: plan, sandbox, data, eval — then benchmark honestly.

01 / DEPTH
Plan before burn
Scope the experiment so cycles go to the claim, not the scaffolding.
02 / DEPTH
Eval in the local loops
Engineering and AI loops share isolated runs — verdicts you can replay when models or data shift.
03 / DEPTH
Attach any provider
Local weights or OpenAI-compatible APIs — swap without rebuilding the harness.
04 / DEPTH
Benchmark across setups
Keep the harness fixed while you compare models and configs.
  • 01 / SPEC
    Sandbox runs with clear eval receipts
  • 02 / SPEC
    Data generation + benchmarking in one loop
  • 03 / SPEC
    Attach local models or your API provider

Get notified when it ships.

Join the waitlist — we will reach out when ML Harness opens.

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