Building an Agentic Intent Data Foundation for with Infrahub

Network and infrastructure teams are increasingly moving towards agentic automation, aiming for AI agents capable of handling various network tasks autonomously. However, a significant challenge lies in the underlying data not being structured for agent consumption, leading to difficulties in synthesizing information across disparate systems. To address this, an AI-ready intent data foundation is needed, characterized by structured, relationship-rich data that can be reliably queried, stays current with network changes, and is tailored to specific organizational topologies. Infrahub is designed to serve as this foundational layer, integrating and enriching data across devices, services, and customer relationships using a knowledge graph architecture. It offers a GraphQL API and MCP interface to simplify agent queries and includes governed change processes to minimize data drift. Infrahub Skills, an AI package, aids teams in developing valid schemas and automation logic, facilitating faster implementation and ongoing optimization. Companies leading in agentic automation are proactively building these foundations, using tools like Infrahub to establish a scalable, agent-ready data model that supports efficient network management.