DataOps for AI

Access the data, wherever it lives, across all your industrial and enterprise systems. Industrial data lives across PLCs, OPC servers, MES, CMMS, and ERP systems, historians, MQTT brokers, SQL databases, and cloud lake houses. These are spread across lines, networks, plants, cloud, and vendor applications with no standard interfaces. AI agents require access to this data to be consolidated into a set of simple MCP-based tools from a single MCP server. 

Control what agents can have access to and what they can do. As agent usage grows, governance stops being optional. Connection authentication and authorization of which agents can call which tools is critical. You also need insulation from change. LLMs evolve weekly, agent platforms pivot, and MCP is still maturing. The work you do today should not be hostage to vendor decisions made yesterday. A well-designed Industrial DataOps layer keeps your tool definitions, data products, and governance policies stable while everything above the data layer evolves and optimizes. That is the difference between an experiment and enterprise infrastructure.