AI Center of Excellence from Scratch

Client

Who We Worked With

A large enterprise that wanted AI capability in-house but had no team, no operating model and no AI best practices in place.

Problem

The Business Problem

The organization wanted AI capability in-house but had no team, no operating model and no AI best practices. Typical industry practice: hire slowly, learn by trial and error, stay dependent on vendors.

Baseline

Where They Started

• No dedicated AI team or CoE
• No defined AI operating model or governance
• No in-house AI delivery playbooks or best practices
• Heavy dependency on external vendors for any AI initiative

Data

Data Sources Used

• Current org structure, roles and skills inventory
• Existing technology stack and data platforms
• Active AI use cases and pilots across business units
• Internal compliance, security and procurement standards

Solution

What We Built

NeoBram designed and stood up the AI CoE end to end: structure, hiring, governance and delivery model, plus hands-on developer training in AI best practices and using AI to multiply their own productivity.

Integration

Systems We Connected

• CoE operating model aligned to existing enterprise governance
• Hiring profiles and onboarding plan for AI and ML roles
• Delivery playbooks for discovery, build, MLOps and run
• Developer enablement program embedded into daily workflows
• Executive scorecards to track CoE maturity and outcomes

Timeline

Project Timeline

Operating model and first hires in 8 weeks. 35 dedicated CoE members onboarded and productive within 6 months.

Governance

Security & Compliance

• CoE structure aligned with enterprise risk and compliance
• Clear RACI between CoE, business units and central IT
• Hands-on developer training in responsible AI use
• Knowledge and IP retained in-house, not with vendors
• Independent client ownership of the operating model and playbooks