Primary offer
AI Ops Diagnostic
Map the workflow before you automate it.
A practical diagnostic for teams with scattered intake, manual triage, document review, guest or customer requests, approval delays, or unclear AI risk. The output is a workflow map, risk gates, automation candidates, and a pilot plan that keeps human judgment in the path.
Best fit
Where this helps
- Teams with repetitive intake, handoffs, approvals, or triage work that still depends on judgment.
- Operators who want useful AI but do not want a black-box automation push.
- Hospitality, service, local business, and document-heavy teams that need a first safe pilot.
How it runs
- Capture the current workflow, inputs, exceptions, systems, owners, and approval points.
- Separate routine work from high-risk decisions that need human review.
- Rank automation candidates by value, risk, data readiness, and operational friction.
- Define the smallest pilot that can be measured without disrupting the business.
What you get
- Workflow map with handoffs, bottlenecks, failure points, and ownership gaps.
- Risk-gate map showing what AI can draft, what a rule can decide, and what a person must approve.
- Automation candidate list ranked by impact, risk, and implementation path.
- Pilot plan with scope, data needs, success measures, and next-build sequence.
Guardrails
- No production automation recommendation without a human approval path where risk is high.
- Prototype, sample-data, and production boundaries stay visible.
- Success measures are operational and observable, not inflated ROI promises.
Proof bridges
Have a workflow that looks close to this?
Send the messy version. The first useful step is usually deciding what should be mapped, what should be tested, and what should stay human-owned.