Assembly Verification AI with ERP and MES
Tie AI inspection to ERP, MES, and QMS for serial-level traceability, automated holds, rework routing, and real-time cost updates.
Tag
AI Strategy
Articles tagged “AI Strategy” on Ryshe.
Why Operator Copilots Fail at Handoff
Copilot escalations fail from missing plant context, poor routing, and buried controls. Fix with structured handoffs, routing, and audits.
Azure AI Quota Tracking for Shared Hubs
Track TPM, PTU, VM family and deployment quotas in shared Azure AI hubs using Foundry, Monitor, and Log Analytics; set alerts and owners.
Return Visit Triggers in Dynamics 365 Field Service
Status-based triggers and structured fields turn return visits from costly guesswork into automated, trackable follow-up workflows.
Monitor Azure AI Inference with OpenTelemetry
Use OpenTelemetry and Application Insights to monitor Azure AI inference—track traces, p95 latency, token usage, errors, and audit tags from the first request.
Evaluate Copilot Task Success in Copilot Studio
Define pass/fail rules, run test sets, inspect traces and verify end states to ensure AI copilot tasks truly complete.
Why We Stopped Selling AI Projects and Started Delivering Continuously
We kept watching good AI work stall the day a project ended. So we changed the model. This is the case for continuous AI delivery — and what it means for clients.
Why We Don't Publish AI Pricing — and What to Ask on the Call Instead
A price on a page is easy to compare and almost always wrong for real AI work. Here's why we scope on a call, and the questions that actually predict cost and value.
Forge or Labs: When to Run AI Continuously vs. as a Project
Some AI work is a steady roadmap; some is a dedicated build with a finish line. Knowing which is which saves money and momentum. Here's how we decide.
Start Small, Then Build Big: The Case for Land-and-Expand AI
The biggest AI builds rarely start big. They start with a focused win, earn trust, and expand once the partner already knows your systems. Here's why that sequence works.
Building an AI Center of Excellence Without Hiring a Data Science Team
Most mid-market companies can't justify a full AI team — and don't need one. Here's how to build the governance, momentum, and skills of a center of excellence without the headcount.
Reserved Capacity: Treating AI Delivery Like a Utility, Not a Headcount
Hiring for AI is slow and risky; one-off projects stall between phases. Reserved monthly delivery capacity is a third option — and it changes how the work flows.