Bring human-level cognition to your
data

Mapping the relationships behind your data—including people, projects, and processes—to power context-aware enterprise AI. Glean’s knowledge graph understands and connects all your enterprise content, people, and activity, helping you instantly find the answers you need.

Personalized for each enterprise

Glean learns how your organization works, enabling you to leverage content and context unique to your company. It understands which applications are most used and how, which data informs decisions and sparks discussions, how users collaborate, and even the acronyms you use. 

Captures diverse preferences

Glean diverse user preferences like:

  • Authoritativeness (“what’s our latest  benefits plan?”)
  • Personal (“find last week’s meeting notes”)
  • Recent (“provide an update of the latest outage”)

Find the most relevant content for your question, make real progress instead of searching.

In-the-know on how you work

Glean’s knowledge graph learns and adapts along with you and your organization. As teams change, your network grows, and projects shift, Glean constantly keeps up and provides you with the most relevant information for each query.

Equip employees and agents alike with multi-hop reasoning

AI needs context to handle complex tasks the way humans do. When we look at information, we naturally connect it to related work, people, and projects. To make that connection, AI requires knowledge graphs to organize the relationships in data—enabling pattern recognition and intelligent action. 

Go beyond a surface-level understanding of your content

Knowledge graphs identify high-quality nouns in the data and map them to known entities—such as projects, people, customers, and products. Each entity is supported by a network of related signals—for example, all the documentation, support tickets, and feature specs connected a certain product. The network goes beyond surface-level semantic understanding and provides nuanced context. This enables the system to distinguish between specifics, such as similar product names like Gemini 2.0 Flash and Gemini 2.0 Pro.

Protect your data with a graph built 
for your enterprise

Building knowledge graphs in the enterprise requires indexing not just content, but also the rich metadata that feeds meaningful signals into the graph—something that depends heavily on the quality of underlying connectors. Glean builds these graphs entirely using machine learning by understanding the data structures of enterprise apps and automatically inferring entities. All of this happens within each customer’s single-tenant environment for data privacy. 

Make AI work for every employee and every task

While knowledge graphs organize data, personal graphs focus on how individuals across the organization really work.. By looking at actions across apps, personal graphs can infer the broader tasks and projects behind them. This gives models a higher-level view of work. By understanding what someone works on and how they get things done, Glean can better personalize agents to help.

Create agents that reflect how your people and enterprise work

The knowledge graph and personal graph capture two of an enterprise’s most valuable assets: data and people. Because people drive core processes, mapping their interactions helps us uncover process knowledge that can guide AI agents.

One of the beauties of these graphs is their dynamic nature—they evolve with the changing relationships, roles, and workflows, helping us reflect the fluid, nuanced reality of work.

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