What Is a Context Layer?

A context layer functions as an essential infrastructure component between SaaS APIs and AI agents, managing authorization, normalization, and real-time delivery of business records crucial for agent actions. Unlike semantic layers or RAG pipelines, the context layer addresses the need for up-to-date information, enabling agents to make informed decisions based on current data rather than stale records, which is critical in situations where incorrect actions can have significant consequences. It ensures real-time reads from source APIs, enforces authorization at access time, normalizes data across different platforms, and delivers event-driven updates, distinguishing it from basic data access APIs that only provide queried records without embedded authorization or normalization. The context layer's role in the AI stack is to provide real-time, authorized, and normalized access to live business records, ensuring that AI agents can operate effectively by reacting to changes immediately, which is increasingly becoming a standard in enterprise AI architecture. Unified's API layer and MCP server exemplify this by offering real-time, authorized data access and delivering change events without storing customer data, ensuring agents have consistent and current information across various SaaS platforms.