Inside the Firewall: MCP-Powered Paths to Enterprise AI That Respect Your Data

Most enterprise AI deployments have a dirty secret: they work by moving your data to AI.

That means your data assets, operational records, infrastructure data, and sensitive internal files leave your control. Even if just temporarily, even if “encrypted,” even if your vendor promises it’s safe.

There’s a better architecture with FME. And it changes everything.

The Model Context Protocol (MCP) inverts the model: instead of your data going to AI, AI comes to your data. Querying it through a controlled, governed interface without ever ingesting it. In this webinar, we demonstrate exactly how this works across two real-world deployment patterns using FME’s MCP Server, built to handle 450+ formats, and systems including spatial, CAD, BIM, and legacy enterprise data.

Pattern One: Cloud AI, Shielded Data

• Connect leading cloud AI agents to your on-premises spatial and operational data through MCP.
• Shield your data so the AI gets answers yet doesn’t have direct access to sensitive data. Your data never moves. Your compliance team stays calm.

Pattern Two: Total Sovereignty

• Pair on-premises models like Gemma 4 with MCP Servers hosted on your internal FME data infrastructure.
• For organizations where even the question can’t leave the building. No cloud. No exposure. No compromise.

If your organization sits at the intersection of serious data governance and serious AI ambition, this is the session you’ve been waiting for.