The enterprise AI stack is being rebuilt.
Models are becoming more capable, and increasingly interchangeable. As AI moves from answering questions to doing mission-critical work, the constraint is no longer raw intelligence. It is organizational context: understanding how a company operates, what information matters, and what should happen next.
Without that context, enterprises get shallow answers, rising token costs from sending irrelevant information to expensive models, and AI sprawl as teams adopt disconnected tools. The answer is not simply more models. It is an intelligence layer that understands the organization and routes each task to the right model, agent, and workflow.
That is the thesis behind the 50+ new features weโre announcing today at
@Glean:GO, including:
๐๐น๐ฒ๐ฎ๐ป ๐ง๐ฎ๐: A new governed desktop AI workspace that combines an open agent harness with your enterprise context, unifying local files, applications, browser workflows, and code repositories in one workspace. That context is what lets agents delegate complex, multi-step work and deliver better performance, while respecting permissions.
๐๐น๐ฒ๐ฎ๐ป ๐๐ป๐๐ฒ๐น๐น๐ถ๐ด๐ฒ๐ป๐ฐ๐ฒ: Uses organizational context to route each task to the right model, while giving enterprises control over quality, usage, and cost. Our benchmark found that Glean reduced token costs by 81% as compared to Claude Cowork, and was preferred 78% of the time.
๐๐น๐ฒ๐ฎ๐ป ๐ง๐ฟ๐ฎ๐ป๐๐ณ๐ผ๐ฟ๐บ: Built on your Enterprise Graph, it understands how work happens across your organization, identifies the best opportunities for AI, recommends the right agents and skills, and measures the impact on your business.ย
To help us announce these new capabilities, Iโm looking forward to being joined by leaders from some of the worldโs most innovative organizations, including
@GM,
@nvidia,
@Snowflake, and
@OpenAI, who will share how they are using Glean in mission-critical workflows.
See you today at Glean:GO in San Francisco and online.