Fractional Chief AI Officer
82% of AI never reaches production.
Not from bad technology. From no operating model. RIG gives complex organizations a governed route from a promising pilot to an auditable production decision.
The problem
Pilot success is not production readiness.
Real data, actual users, regulation, and an accountable operator arrive after the demo. That is where most AI initiatives stall.
RIG makes those constraints visible before they become expensive. Each gate is a commitment, not a checkbox.
Pilot optimism.
Success is inferred from a controlled demonstration rather than measured in an operating environment.
A named owner.
Risk, data quality, and adoption become specific decisions with clear accountability.
A decision trail.
The system has a measurement cadence, an evidence record, and a responsible next action.
The system
Twelve gates. One inspectable route to production.
Intake
Decision: capture the business outcome, constraints, owner, and failure modes before a model is selected.Question
Decision: frame the business question whose answer would create measurable value.Research
Evidence: ground relevant claims in primary sources, operating data, and explicit uncertainty.Synthesize
Decision: compress the evidence into one strategy with stated trade-offs and accountable owners.Quantify
Guardrail: define the metrics, budget, risk thresholds, and kill criteria before production work begins.Produce
Artifact: build the smallest production-grade system that can prove the decision.Iterate
Check: test failure modes, inspect bias, and adjust the system against the gate criteria.Verify
Proof: confirm the real artifact passes the real done-test, with evidence available for review.Ship
Release: deploy with an operator, observability, rollback path, and runbook.Measure
Signal: compare production results with the quantified criteria on a defined cadence.Learn
Record: capture failures, surprises, and decisions so the next run begins with evidence.Evolve
Renew: revisit the system as data drifts, models age, and business conditions change.
Selected outcomes
Evidence is part of the operating model.
$32B
Integration program
Regulatory-grade diligence pipeline for a healthcare transaction program.
Evidence reviewed in the assessment under NDA.130K
Patient environment
Operating context involving structured and unstructured clinical records.
Evidence reviewed in the assessment under NDA.3h→15m
Decision workflow
Measured compression of a manual underwriting review cycle.
Evidence reviewed in the assessment under NDA.GWU
Research recognition
Academic collaboration and external research validation.
Evidence reviewed in the assessment under NDA.Where it applies
Built for complex operations, not a generic AI playbook.
Regulated care
Healthcare, dental, and orthopedics where evidence, privacy, and operator accountability are non-negotiable.
Physical operations
Manufacturing and construction where data meets safety, asset reliability, and distributed teams.
High-trust services
Legal, accounting, and professional services where decisions need an audit trail and a clear owner.
The ladder
Assessment → Audit → Build. One sequence.
Assessment — free, 30 minutes
Which of your three most consequential decisions are governed well enough to automate. No slides, no pitch. The free entry step that decides whether the rest of the ladder is worth paying for.
Audit — priced after a short conversation
A three-page judgment map, not a slide deck: the decision inventory, the data-source check, and a kill number for each decision. That is what separates a build you can defend in a board meeting from another pilot you have to apologize for.
Build — 90 days, priced after a short conversation
One judgment loop, live end to end, with its disconfirming test written down before the work starts and a decision-evidence record an operator can audit without a data team. The fractional expansion path ships inside the build package as its fourth month — it is a delivery of this build, not a separate engagement. No fourth public CTA; the offer stays at three.
The next decision
Stop wasting. Start shipping.
Use 30 minutes to identify the gate that is holding your AI program back and the evidence required to clear it.
Start the 30-minute assessment