Glean’s Enterprise Search Push Is Cornering Guru’s Knowledge Base

Glean Is Eating Guru’s Lunch

Glean, the enterprise search startup backed by Sequoia and Lightspeed, is pushing aggressively into territory that knowledge base platforms like Guru have spent years building. The question is whether Guru can hold its ground when the search layer and the knowledge layer are collapsing into one product.

When Search Becomes the Product

Glean started as a connector – a smart search tool that could surface answers from Slack, Confluence, Salesforce, and dozens of other enterprise apps. That pitch was clean and non-threatening: Glean would sit on top of your existing tools and make them findable. Knowledge base vendors like Guru, which built their businesses on structured, human-curated cards of company information, did not initially see Glean as a direct competitor. That changed.

Glean has steadily added features that blur the line between search and knowledge management. Its AI-generated answers now synthesize content across sources and present it in a format that looks very much like a knowledge card – organized, cited, and easy to share. When Glean can answer “What is our refund policy?” by pulling from a Google Doc, a Zendesk ticket, and a Slack thread, the business case for maintaining a separate, hand-curated knowledge base weakens considerably. Why pay for Guru to store a card about the refund policy when Glean is already surfacing the right answer from live sources?

The deeper issue is that Glean is compressing the workflow. In the traditional setup, an employee searches, finds a Guru card, reads the card, and acts. With Glean, the search and the answer happen in the same moment. That is not a minor convenience improvement – it is a direct attack on the value Guru charges for. Guru’s product is the organized, verified, human-maintained answer. Glean’s product is getting to the answer faster, regardless of where it lives.

Glean’s funding tells part of the story. The company raised a $200 million Series D in 2024 at a $4.6 billion valuation, and it has been pouring that capital into expanding its AI reasoning capabilities, its admin controls, and its permissions architecture – three areas that historically gave enterprise buyers reason to hesitate before trusting a search tool with sensitive data. Those hesitations are fading as Glean’s compliance and security posture matures.

What Guru Actually Does Well – and Where That Gets Complicated

Guru’s core argument has always been about trust and verification. Search engines surface information; Guru surfaces verified information. The platform’s card system is built around the idea that someone – a human, usually in HR, operations, or revenue enablement – has reviewed and approved the content. That review cycle creates accountability. When a sales rep needs to quote a pricing policy in front of a customer, the difference between an AI-synthesized answer and a card that was reviewed by the CFO last Tuesday is not trivial.

That verification layer is genuinely difficult for Glean to replicate. Glean can surface the most recent pricing document, but it cannot easily signal that a human with authority reviewed it this week and confirmed it is still accurate. Guru’s product is built around that signal. The card shows when it was last verified and by whom. That provenance matters in regulated industries, in legal-adjacent workflows, and in customer-facing contexts where bad information carries real cost.

The complication is that most enterprise knowledge does not live in those high-stakes categories. The majority of searches across a company are about internal processes, product specs, meeting notes, and onboarding information – areas where the verification layer adds friction more than it adds value. Glean wins easily in those zones, and those zones represent the bulk of daily search volume inside any company. Guru gets to keep the edge cases. Glean takes everything else.

Guru has been aware of this dynamic and has responded with its own AI features, including AI-generated answers that draw from its card library and integrations that try to keep Guru in the workflow even when employees start their search elsewhere. The company has also leaned into its role as a single source of truth, positioning the structured knowledge base not as a search tool but as a content governance platform. Whether that repositioning lands with buyers is an open question. Enterprise buyers already stretched thin on SaaS spend are increasingly skeptical of tools that require active maintenance to stay valuable.

There is also a distribution problem. Glean sells to IT and operations leadership with a broad enterprise search pitch, then expands across departments. Guru typically enters through revenue enablement or customer success teams and struggles to grow beyond those initial buyers. That means Glean often gets the enterprise-wide contract before Guru ever gets a chance to prove its verification value at scale. The sales motion difference is not about product quality – it is about who controls the budget and who gets the meeting first. This dynamic mirrors what is playing out in other AI-adjacent markets, like Airtable’s expansion into Smartsheet territory, where platform breadth is outrunning specialized depth.

The Platform Gravity Problem

The structural pressure on Guru goes beyond any single feature comparison. When a company buys Glean, it buys into a platform with deep integrations, admin controls, and an expanding surface area. Glean is not trying to replace Guru specifically – it is trying to become the layer through which employees interact with all work knowledge, and Guru is simply one of the sources that gets absorbed into that layer. Platform gravity works this way: once Glean becomes the default search interface inside a company, every point solution it can replicate becomes harder to justify as a separate line item.

Guru’s best defense is probably not a feature race – it is a sharper articulation of why governed, verified knowledge is worth maintaining separately from whatever the AI search layer surfaces. That argument is strong in specific contexts and weak in most others. The market will decide how many of those specific contexts are worth a dedicated budget line, and right now, that number appears to be shrinking.