AWS is introducing AWS Context, a new service that automatically maps the relationships across existing data into a knowledge graph and provides agentic search so AI agents in the organization can access governed data relationships, business rules, and domain knowledge at runtime.
According to AWS, data stewards and curators manage the graph through an intuitive console experience, reviewing inferred relationships, promoting them to production, and attaching domain-specific knowledge such as business definitions and usage rules.
AWS Context extends the same knowledge graph technology that powers Amazon Quick, where hundreds of thousands of users interact daily with a production knowledge graph that catalogs datasets, dashboards, and metadata, learning from usage patterns to make every interaction smarter. That graph already processes millions of requests per day.
With AWS Context, the company is extending what was a personal knowledge graph into an organizational one, a shared, governed context layer that agents and applications in the organization can draw from.
Existing Amazon Quick users benefit immediately. When AWS Context is enabled, Quick’s agents gain access to the broader enterprise knowledge graph, including cross-system relationships, business rules, and curated context that go beyond what any single user’s personal graph can provide, the company said.
AWS Glue Data Catalog, Amazon SageMaker Unified Studio, and AWS Lake Formation integrate with the knowledge graph, so teams can govern it with business rules and permissions and add new context automatically with AI assistance or explicitly through manual curation.
Key elements of the context layer are published to Amazon S3 in the Apache Iceberg format, so that customers are free to use the Iceberg-compliant tools of their choice to consume metadata and build against AWS Context based on open standards.
Additionally, AWS announced the preview of business context and semantic search for AWS Glue Data Catalog, providing context and tools that make it easier for humans and AI agents to discover and understand data.
Customers can now enrich their Glue tables, views, and columns, including those backed by S3 Tables, with business descriptions, glossary terms, custom metadata, and associate them with skill assets that provide additional data context stored outside the catalog. With business context indexed alongside technical metadata in Glue Data Catalog, customers can use the new Glue Search API to more quickly find data by business meaning and AI agents can ground their reasoning in trusted definitions rather than inferring context.
“Context is the data lake for AI agents, and with these innovations, we are building the foundation of knowledge and intelligence for AI agents interacting with data across organizations and enterprises of any scale,” said AWS.
For more information about this news, visit https://aws.amazon.com.