The boring, high-volume, measurable problem is the point. Routing, QA, maintenance, scheduling — the work that repeats every day.
Based on the vertical playbooks and operating patterns in AI That Pays for Itself.
The book uses UPS ORION as the archetype: repetitive operational decisions at huge scale.
Shop-floor wins come from vision, sensors, and process discipline pointed at defects, downtime, and throughput.
Manufacturing already has metrics. AI belongs where it can move them, not where the demo looks clever.
Pick one workflow. Score readiness. Estimate current cost. Write the kill criterion before the pilot starts. If that sounds obvious, good. Obvious is usually what ships.
Implementation partner
I set the AI strategy and govern the work — I do not try to do everything myself. When a project is ready to build, I bring in my implementation partner, Olyra, to execute. You get the plan and the team to ship it.
See how Olyra implements →