Capture
Show us the real job: trigger, tools, steps, decisions, exceptions and expected result.
AI workflow deployment, with evidence
Before AI touches production,
make it prove the work.
Record one repetitive workflow. We reconstruct it as a shadow operator, run it beside your current process, and measure correctness, exceptions, time and cost before anything earns permission to act.
Production writes off by defaultHuman approval gatesEvery run leaves evidence
The operating model
Shadow → prove → promote.
Most automation projects jump from demo to deployment. OperatorProof inserts a measurable operating stage between them.
Reconstruct
We turn the work into an executable job definition with explicit boundaries and approvals.
Shadow
The AI handles copies of real work while every consequential write remains suppressed.
Score
Compare AI and human outcomes on correctness, completion, latency, cost and exceptions.
Promote
Only steps that clear agreed proof gates receive narrowly scoped production permission.
What we sell
Completed work.
Not AI theater.
Baseline first
Measure how the job works today before claiming improvement.
Least privilege
Read-only and dry-run access first. Production permissions are earned, not assumed.
Exceptions are data
Disagreements become test cases instead of getting hidden inside a success percentage.
Humans keep authority
Money movement, sensitive records and other consequential actions stay gated.
Free workflow intake
Give us one job your team repeats.
We’ll establish the baseline and return the first safe shadow-pilot plan. This preview does not make invented savings claims.
01
You describe the real workflow.
No AI jargon required.
02
We identify the proof boundary.
What can be shadowed, what needs approval.
03
Evidence decides what ships.
No production autonomy from a demo.