The enterprise AI land grab is on. Glean is building the layer beneath the interface.

The enterprise AI land grab is on. Glean is building the layer beneath the interface.

The battle for enterprise AI is heating up. Microsoft is bundling Copilot into Office. Google is pushing Gemini into Workspace. OpenAI and Anthropic are promoting on to enterprises. Every SaaS vendor now ships an AI assistant. 

In the scramble for the interface, Glean is betting on one thing less seen: turning into the intelligence layer beneath it. 

Seven years in the past, Glean set out to be the Google for enterprise — an AI-powered search tool designed to index and search across a company’s SaaS tool library, from Slack to Jira, Google Drive to Salesforce. Today, the company’s strategy has shifted from building a better enterprise chatbot to turning into the connective tissue between fashions and enterprise programs.

“The layer we built initially – a good search product – required us to deeply understand people and how they work and what their preferences are,” Jain told TechCrunch on last week’s episode of Equity, which we recorded at Web Summit Qatar. “All of that is now becoming foundational in terms of building high quality agents.”

He says that while large language fashions are highly effective, they’re also generic. 

“The AI models themselves don’t really understand anything about your business,” Jain said. “They don’t know who the different people are, they don’t know what kind of work you do, what kind of products you build. So you have to connect the reasoning and generative power of the models with the context inside your company.”

Glean’s pitch is that it already maps that context and might sit between the mannequin and the enterprise data. 

The Glean Assistant is often the entry point for purchasers — a well-known chat interface powered by a mixture of main proprietary (ie, ChatGPT, Gemini, Claude) and open-source fashions, grounded in the company’s inner data. But what retains prospects, Jain argues, is all the pieces beneath it. 

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First is mannequin entry. Rather than forcing corporations to decide to a single LLM supplier, Glean acts as the abstraction layer, permitting enterprises to change between or mix fashions as capabilities evolve. That’s why Jain says he doesn’t see OpenAI, Anthropic, or Google as competitors, however quite as companions. 

“Our product gets better because we’re able to leverage the innovation that they are making in the market,” Jain said. 

Second are the connectors. Glean integrates deeply with programs like Slack, Jira, Salesforce, and Google Drive to map how info flows across them and allow brokers to behave inside those instruments. 

And third, and maybe most important, is governance. 

“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,” Jain said. 

In large organizations, that layer will be the distinction between piloting AI options and deploying them at scale. Enterprises can’t merely load all their inner data right into a mannequin and create a wrapper to type out the options later, says Jain. 

Also essential is guaranteeing the fashions don’t hallucinate. Jain says its system verifies mannequin outputs against source paperwork, generates line-by-line citations, and ensures that responses respect current entry rights. 

The query is whether or not that center layer survives as platform giants push deeper into the stack. Microsoft and Google already management a lot of the enterprise workflow floor space, and so they’re hungry for more. If Copilot or Gemini can entry the same inner programs with the same permissions, does a standalone intelligence layer still matter?

Jain argues enterprises don’t wish to be locked right into a single mannequin or productiveness suite and would quite go for a impartial infrastructure layer quite than a vertically built-in assistant.

Investors have purchased into that thesis. Glean raised a $150 million Series F in June 2025, practically doubling its valuation to $7.2 billion. Unlike the frontier AI labs, Glean doesn’t want large compute budgets.

“We have a very healthy, fast-growing business,” Jain said.

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