Trace
See the work as it really happens.
Current-state trace + measured baselineObserve the live workflow, interview the people inside it, and baseline time, volume, errors, delay, cost, and consequence before choosing technology.
01 / FIELD METHODTRACE → CHOOSE → BUILD → PROVE
Make the work
visible first.
AI does not repair a workflow nobody understands. We begin with the real work, make one evidence-backed decision, and earn every phase that follows.
Bring a workflowTHE FOUR-PART OPERATING LOOP
Evidence before expansion.
Choose
Pick the constraint worth solving first.
Build / buy / simplify / leave-alone decisionRank value, feasibility, data, risk, and adoption. Recommend a build only when there is a measurable path to recovering the investment.
Build
Make the smallest reliable fix real.
Working system + evaluation set + review pathBuild against representative cases, connect the existing tools, protect access, and design human review and exceptions before going live.
Prove
Measure the gain and make the work stick.
Before / after scorecard + runbook + next decisionDual-run the workflow, seed failures, train the operator, compare the result with the baseline, and make the next decision from evidence.
WHAT “PROVE IT” MEANS
Four dimensions. One honest decision.
A faster demo is not enough. The system has to work, move an operating number, protect quality, and leave a capable operator behind.
Effectiveness
Did the workflow complete the intended job on representative work?
Efficiency
Did elapsed time, touches, queue time, or staff effort actually move?
Quality
Did errors, rework, completeness, and exception handling improve?
Capability
Can a named operator understand, verify, override, and recover?
THE BUILD / BUY / SIMPLIFY / LEAVE-ALONE GATE
“Do not build” is a useful result.
If the opportunity cannot clear value, feasibility, data, risk, and adoption, the assessment should say so. The blueprint is still yours.
See the engagements ↗