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Glean, AI in search of enterprise knowledge

L’essentiel

Founded in the United States in 2019, Glean develops an AI-powered search and assistance platform connected to enterprise tools. Its approach involves tapping into internal knowledge to find information, produce a summary or help with a task, while taking employees’ access permissions into account.

À retenir

Founded in the United States in 2019, Glean develops an AI-powered search and assistance platform connected to enterprise tools. Its approach involves tapping into internal knowledge to find information, produce a summary or help with a task, while taking employees’ access permissions into account.


Glean is an American software company based in Palo Alto, California, specializing in information retrieval and artificial intelligence for businesses. Available at glean.com, its platform connects workplace applications so their content can be searched through a single interface. It addresses an everyday problem: useful knowledge is scattered across documents, messaging services, project management tools and knowledge repositories, each with different access rules.

Roots in information retrieval

Founded in 2019, Glean counts Arvind Jain, a former Google engineer and co-founder of data protection specialist Rubrik, among its co-founders. The company emerged from the observation that finding internal information becomes difficult as organizations adopt more software and expand their teams. Its search engine launched publicly in 2021, before the rise of generative AI transformed user expectations.

These origins explain its positioning: rather than offering only a general-purpose conversational agent, Glean focuses first on organizing access to enterprise knowledge. Search thus forms the foundation of its assistance and automation features.

Connecting applications, contextualizing answers

Glean offers connectors to services such as Google Drive, Microsoft 365, Slack, Salesforce and Jira. The platform indexes content and draws on its context, particularly the relationships between documents, people and activities. The aim is to provide relevant results based on the question asked and the user’s work environment, without requiring them to know a file’s exact location.

This search capability is complemented by generative AI features: natural-language answers, document summaries, writing assistance and assistants tailored to specific roles. Glean combines the retrieval of internal information with language models, using an approach commonly known as retrieval-augmented generation. Answers can link back to the sources used, allowing them to be verified. The offering also includes tools for creating agents designed to chain actions together and automate processes.

Permission management is central to this architecture: results must respect the access rights defined in the source applications. For IT departments, confidentiality and governance are just as important as answer quality.

What next?

Glean operates in a market where office productivity suites and cloud platforms are integrating their own assistants. Its differentiation rests in particular on its ability to connect heterogeneous software environments rather than favor a single ecosystem. The development of agents opens up uses beyond consulting documents, but also increases oversight requirements.

What comes next will depend on concrete results: the reliability of the information provided, the relevance of automations and adoption by teams. For its customers, the challenge will be to turn easier access to internal knowledge into measurable operational gains, without neglecting data quality or human oversight.

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