Agents are only as intelligent as the context they can reason over. Today, that context is scattered across data lakes, data warehouses, lakehouses, databases, and streams, and in institutional knowledge that has never been written down. You want to trust the decisions made by your AI agents, but that can’t happen until agents have context. Imagine what becomes possible when we give agents a safe way to access the context they need to deliver trusted decisions.
This is why at the AWS Summit New York City, we’re announcing a series of innovations that deliver intelligence for your data and AI agents at scale.
AWS Context (Coming soon)
In today’s keynote, we introduced AWS Context, a new service that automatically maps the relationships across your 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. Data stewards and curators manage the graph through an intuitive console experience, reviewing inferred relationships, promoting them to production, and attaching domain-specific knowledge like 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, we are extending what was a personal knowledge graph into an organizational one, a shared, governed context layer that agents and applications in your 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. 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.
