Map
Tools, handoffs, and failure points — how work actually runs today across CRM, meetings, sheets, and people.
PROCESS
How we put AI systems into production.
No mystery process. Diagnostic first, build second. We map and quantify the bottleneck, pick one pilot in writing, build under production constraints, then run with guardrails — and your team approves anything that matters.
THE STEPS01 02 03 04 05 06 07 08
Eight stages, clear handoffs.
Quantify
Hours, error cost, and tool cost in your numbers — so the pilot is chosen for ROI, not vendor fashion.
Diagnostic report + pilot pick
Written systems map, where AI pays, 90-day roadmap, and one recommended pilot with a rough build estimate.
Scope in writing
Acceptance criteria, credentials checklist, test plan, and price — agreed before any production build starts.
Build in production constraints
Auth, renewals, monitoring, and failure modes. Tool follows the work — n8n, Graph, HubSpot, LLMs, or custom code.
Test edge cases with the client team
No-match paths, internal vs external meetings, permission edges, and silent-failure modes. Your team approves what matters.
Launch + train
Go live on the agreed path, train the people who will run it, and hand over docs.
Run and improve
Optional AI Ops retainer: monitoring, drift checks, capped changes, and monthly ROI notes — not open-ended body rental.
TIMELINE NOTE
Clocks start after access and decisions.
Missing credentials, missing access, slow approvals or unclear scope will delay launch.
Your team still owns the facts, business decisions, customer promises and final approvals.
NEXT STEP
Start with a Diagnostic.
Bring the CRM, meeting, or ops bottleneck that is burning hours.