AI Business Integration

The problem

Most AI projects die at the same boundary: the proof-of-concept worked, but nobody could figure out how to wire it into the systems where the actual work happens. The RAG prototype ran on laptop files. The Copilot pilot ignored SharePoint permissions. The agent demo never touched the CRM.

What we do differently

We start at the integration boundary and work backward. Before a single model call gets made in production, we know: how identity flows, which systems of record matter, what the cost envelope is, what the governance story is, and what the failure modes look like.

What we ship

• RAG deployments over your actual document stores (SharePoint, Confluence, Notion, S3, Drive) with respect for existing permissions.
• M365 Copilot rollouts — tenant prep, Purview / data loss prevention wiring, pilot cohort selection, measurable success criteria.
• Custom MCP servers exposing your internal tools to Claude, ChatGPT, and other assistants via the Model Context Protocol.
• Agent workflows that actually complete multi-step tasks — with human-in-the-loop escalation paths built in.
• AI governance and usage policy — the adult conversation most vendors skip.

Typical engagement

Four to eight weeks. One or two integration targets. Success measured in production usage — not demo applause.