Glean is an AI-powered search tool that was founded seven years ago. Today, it has pivoted to be the AI model-to-enterprise systems connector all enterprises need instead of bolstering enterprise chatbots alone. This shift has put Glean in the center of a rapidly evolving enterprise AI landscape. Its greatest addition though, is that it empowers organizations to understand and harness the full breadth of generative AI capabilities.
In June 2025, the company announced a $150 million Series F funding round. Now, it’s rightfully sitting on a $7.2 billion valuation high. Glean wants to be the “Google for enterprise.” Employee experience It offers an incredibly powerful full-text indexing and search solution that extends over an organization’s enormous growing library of Software as a Service (SaaS) tools like Slack, Jira, Google Drive, Salesforce and many more.
Glean’s unique credential-based approach powers an abstraction layer on top of enterprises. This flexibility allows businesses to easily adopt or integrate multiple AI models as they develop new abilities. This flexibility is especially important in a world increasingly driven by technology, where companies need to be nimble and able to pivot quickly to meet new challenges.
At the heart of Glean’s offering is model access and connectors that enable integration with a variety of systems. In addition, it has a solid governance structure that protects the integrity and confidentiality of the information users have access to. This governance framework reviews model outputs against the original source documents. Most notably, it automatically produces line-by-line citations and ensures that all responses respect current access rights.
This is what Glean’s co-founder Arvind Jain means when he calls for a permissions-aware governance layer.
“You need to build a permissions-aware governance layer and retrieval layer that is able to bring the right information, but knowing who’s asking that question so that it filters the information based on their access rights.” – Arvind Jain.
This governance framework greatly enhances the accountability of responses. It further safeguards sensitive data, guaranteeing adherence to the Security enterprise requirement that many enterprises face.
Glean has come a long way from an intuitive search product to a robust knowledge infrastructure. This adjustment is indicative of the company’s efforts to better engage with users in large enterprises. Jain said that the first layer of search – the one they just debuted – took extensive knowledge of what people do in their workflows and what they want to see.
“The layer we built initially – a good search product – required us to deeply understand people and how they work and what their preferences are.” – Arvind Jain.
While Glean is doing cool and creative things, they’re building on the work that’s been done by others in the market. This collaborative approach helps enhance Glean’s product offerings, Jain noted.
“Our product gets better because we’re able to leverage the innovation that they are making in the market.” – Arvind Jain.
Jain highlighted a critical limitation inherent in AI models:
“The AI models themselves don’t really understand anything about your business.” – Arvind Jain.
This underscores Glean’s role as not just a facilitator of AI capabilities but as a necessary intermediary that contextualizes AI outputs within the specific frameworks of individual businesses.
