Workflow assessment
A focused look at one workflow. We map it, define correctness, and tell you plainly whether it is ready for a model — and what it would take if it is not.
We work with enterprises end to end. We start with the people who do the work, turn their workflows into environments with checkers, and measure whether a model actually does the job before anything ships. People set the standard; the model is held to it.
One engagement, five steps. Every step leaves something you can inspect.
We start with the people who do the work. We sit with your teams, trace the workflow step by step, and write down where judgment lives and where mistakes cost you.
For each step we agree on what a good outcome is: a checker where it can be computed, a rubric where it needs judgment, and expert review where neither is enough yet.
We turn the workflow into a task world a model can act in — your tools, your documents, your edge cases — with the verifier attached.
We run models through it and report pass rate, failure modes, and a documented reliability number. You see where a model helps, where it breaks, and why.
We use the environment to train and evaluate, then hand over the environment, the checkers, and the results, so your team keeps measuring as models change.
A focused look at one workflow. We map it, define correctness, and tell you plainly whether it is ready for a model — and what it would take if it is not.
Environments built from your own workflows, with checkers and rubrics your team can read, run, and extend.
Human data from people who know the work — demonstrations, preference judgments, and reviews — for the parts no checker covers yet.
Re-run your environments as new models arrive, so the decision to switch or upgrade rests on your work, not on a public leaderboard.