Turning Industrial Data into Knowledge with FlowFuse AI and MCP

Most AI pilots don’t stall because of modeling. They stall because production deployment is hard.

Turning industrial data into contextual knowledge requires more than dashboards and pipelines. It requires architecture designed for security, scalability, and long-term maintenance.

This webinar shows what that deployment actually looks like using MCP, Node-RED, and FlowFuse, including a live build connecting FlowFuse Expert to an MCP system in about an hour.

MCP (Model Context Protocol) offers a powerful way to deploy industrial applications that convert data into contextual knowledge. Leveraging it effectively requires the right platform, one that supports security, ease of use, and long-term maintainability.

In this session, we cover:

• The core technology behind the MCP stack and how it is used to connect context to agentic deployments;
• The difference between data and knowledge, and how they must be treated differently as first-class elements in your system;
• How Node-RED and FlowFuse enable secure, scalable agentic deployments; and
• A build process in FlowFuse to connect FlowFuse Expert to MCP systems in as little as an hour.

You get a clearer understanding of both the technology and the deployment patterns required to implement MCP-based systems in production.

If you're responsible for industrial data pipelines, AI initiatives, or enterprise Node-RED environments, this session is designed for you.

Want to apply this approach in your own environment? Book a demo or try it for free.