Rethinking the semantic layer for the AI era

Over the past decade, Hasura has focused on simplifying enterprise data access through a metadata-driven approach, which naturally evolved into a semantic layer that facilitates fast, secure, and effortless data access. The goal was to create a declarative, low-code method for developing data access APIs by using a metadata blueprint that encapsulates business logic, schemas, and permissions in a structured YAML format. This led to the development of a unified semantic supergraph managed by a distributed query engine that compiles requests into suitable GraphQL, SQL, or API calls, while monitoring performance and enforcing security. With the rise of AI, Hasura introduced PromptQL, leveraging their machine-readable business context to enable AI-driven analytics and automation, emphasizing the need for a dynamic, operational semantic layer over traditional static methods to achieve impactful AI-powered business insights.

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