Context is the next data platform—and why context graphs are key to understanding processes

This post introduces the concept of context graphs as a key component for enabling AI agents to understand and automate enterprise processes. It details Glean's approach to building context graphs by focusing on capturing the 'how' of work through detailed observability of activity data across various enterprise tools. The post explains the technical challenges involved, such as deriving higher-level understanding from atomic actions and handling privacy constraints. It positions context graphs as part of a foundational technology stack for agentic automation, working alongside connectors, indexes, and memory to create a new data platform.