Connected glass modules representing coordinated enterprise agent workflows.

AI GCCs & Engineering Pods

Organize dedicated engineering pods around your Microsoft roadmap. Agree on roles, skills, milestones, code ownership, and operating responsibilities, with regular demonstrations and measured quality checks throughout delivery.

Insights & resources

Frequently Asked Questions
What does AI GCCs & Engineering Pods include?
chevron down icon

An agreed team structure, onboarding plan, delivery milestones, documentation, and a clear handover and support model. The scope defines ownership, prerequisites, and acceptance criteria before delivery begins.

How are access and important actions controlled?
chevron down icon

We agree on approved data, user permissions, and tool access before implementation. Important changes retain human approval where needed. Testing covers unusual requests, failed integrations, recovery, and attempts to exceed permissions. The business and technical owners remain responsible for the deployed workflow.

How do we decide whether to expand?
chevron down icon

Compare pilot evidence with the current process and agreed acceptance measures. Review task quality, completion time, errors, and the full cost of operation, including human review and support. Expand only when results justify it, with clear ownership and a practical recovery plan.