Glean Agents understand how your organization works—which is why they can turn a simple natural language prompt into a complete, end-to-end workflow. By tapping into your company’s existing process knowledge, they build on what’s already proven to work.
LLMs lack the enterprise context needed to make grounded decisions. While that context lives in knowledge stores, it takes a powerful search system to retrieve the right information for each task—whether it’s data analysis, Q&A, or finding experts. Glean is designed to support horizontal AI use cases across the enterprise.
Glean’s open, extensible platform gives you the flexibility to bring your own LLM and connect to third-party agents—so you’re always working with the latest models and tools. It’s built to evolve with the AI ecosystem, letting you adopt new innovations as they emerge while enabling agent-to-agent collaboration that breaks down silos across your enterprise systems.
Users start by describing the task they want the agent to perform in natural language. Behind the scenes, Glean works to fully understand the intent—issuing follow-up queries as needed to gather the right context and clarify the goal.
Glean analyzes how your organization gets work done—studying the structure of past workflows to determine the best plan for a new task. It goes beyond simple similarity matching, using hybrid search and signals from workflows like success rate, usage patterns, and recency to guide decisions. This rich process knowledge is then shared with the LLM to inform the creation of a new, context-aware workflow.
Each agent is designed to achieve a specific goal—whether it’s running data analysis, onboarding, or conducting research—each representing a distinct enterprise query pattern. Glean delivers a powerful search experience by deeply understanding these patterns and grounding AI responses in the right enterprise context.
Evaluating agents isn’t just about checking if they got to the right answer—it’s about defining what “good” actually means for each task. At Glean, we seek to evaluate the intent: creativity for writing, helpfulness for resolving issues, coherence for instructional guides. Then we go deeper, assessing how well each step of the agent’s reasoning holds up. To do this at scale, we use LLM judges: language models trained to evaluate agent outputs within specific query classes.
With Glean, you get access to the latest LLM advancements and can connect to a growing network of third-party agents. While Glean makes it easy to build agents in-platform, we know companies will create agents in many places—that’s why we’ve built an open, extensible platform that integrates with leading agent frameworks like Anthropic’s Model Context Protocol, OpenAI Agents SDK, LangChain, and more.
%20copy-min-p-800.webp)
