Context Layer

The Model Context Protocol, or MCP, is quickly becoming part of the enterprise AI conversation. Its appeal is easy to understand. Instead of building a different custom integration every time an AI assistant or agent needs to interact with an external system, MCP provides a standardized way for AI applications to connect to tools, data […]

As enterprise AI moves from experimentation into real workflows, more technology vendors are talking about context layers. The challenge is that the term can describe very different approaches. One platform may specialize in semantic definitions. Another may focus on agent memory. A data catalog may expose governed metadata to AI, while a cloud data platform […]

As organizations connect AI assistants and agents to enterprise data, several familiar parts of the data stack are taking on new roles. Data catalogs organize and govern data knowledge. Semantic layers standardize business meaning. Governance systems define how information should be used. Now, the context layer is emerging as a way to make this knowledge […]

A context layer gives AI systems the business meaning, relationships, trust signals, and rules they need to understand and use enterprise data correctly. Giving an AI assistant or agent access to a database is relatively straightforward. Helping it understand what the data actually means inside your organization is much harder. A table might contain a […]