We record how leading practitioners reason, decide, and execute on hard problems, and turn those sessions into the training and evaluation data your models learn from and are measured against.
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A model can reproduce the polished output of expert work and still miss the judgment that produced it, the read of an ambiguous problem, the option chosen over plausible alternatives, the check that caught a subtle error.
That reasoning happens inside live practice, gets compressed into a deliverable, and is discarded. Web-scale text keeps the conclusion and loses the working, so progress thins out exactly where expertise matters most.
One pipeline, instrumented end to end, so what reaches your stack is both rich and verified.
We map the exact capability or gap with your team, then design the tasks, rubrics, and environments around it.
Vetted experts solve genuine problems while we instrument the full session, every decision, tool call, and recovery.
Layered human review and automated checkers against an 11-criterion bar. Nothing ships unverified.
Structured SFT, preference, RL, and eval data in your schema, with reporting on what actually moved.
Every format frontier teams train and evaluate on, captured from real experts, verified before it ships. No stitching vendors together.
The bar is the product. Every item is machine-verifiable, judged against a fixed 11-criterion rubric, and cleared by layered human review plus automated validation before it reaches you.
From software and security to regulated professional fields, credentialed practitioners in the domains your models need most.
Working notes from building training and eval data for frontier models, grounded in the literature, written from the work.
Why capturing the working, not just the result, is what lifts models on the hardest tasks.
Read noteBuilding tests that measure capability rather than memorization, and survive being trained on.
Read noteThe properties that separate a useful, well-shaped environment from a brittle one.
Read noteHow every item earns its place in a dataset, and what we reject.
Read noteStill have a question?
We scope the capability or evaluation you need, run a small pilot to calibrate quality, then scale. You can commission custom work or pull from review-cleared off-the-shelf datasets.
Credentialed practitioners with real on-the-job experience in their field, not generic annotators. Every contribution passes layered human review plus automated validation before delivery.
SFT, preference/RLHF, agent and computer-use trajectories, RL environments, code, multimodal data, and evals, in your schema, ready to train on.
A fixed 11-criterion bar, machine verification by execution, held-out and contamination-resistant test design, and traceable reasoning behind every accepted item.
You own the deliverables. We work under NDA, isolate engagements, and scope handling to your security requirements.
Bring us the capability you’re trying to move or the gap you need measured. We’ll scope the data, environments, and evaluations to close it, and report back with hard numbers on whether it worked.