Glean Doubles ARR to $200M as Enterprises Scale From Search to Agentic AI

Glean Doubles ARR to $200M as Enterprises Scale From Search to Agentic AI

Key Takeaways

• Glean hits $200M in ARR just nine months after crossing $100M, placing it among the fastest-growing pure-play enterprise software companies of the decade.
• Enterprise-scale usage is surging, including more than 20 trillion tokens consumed annually and a wDAU/wMAU ratio twice the SaaS benchmark.
• The company is expanding globally, deepening partnerships with AWS, Google, and Microsoft, and moving customers from isolated pilots to company‑wide deployments.

Work AI vendor Glean is accelerating at a pace that’s rare even in an AI-saturated market. The company announced it has reached $200 million in annual recurring revenue, doubling from $100 million in under a year. That’s an unusually fast climb for any enterprise software provider, especially one still framed as “pure-play AI.” And while ARR headlines often blur together, the underlying signals here tell a broader story about how enterprises are actually operationalizing AI.

The company’s footprint has more than doubled, with deployments now running across North America, Europe, and Asia-Pacific. Glean says more than 1,000 employees and customers in over 27 countries rely on its platform to search, reason, and automate work. It’s a lot of growth in a tight window. A small aside: the geographic expansion matters more than companies sometimes admit, because AI adoption creates different compliance and operational headaches depending on the region.

The core of Glean’s pitch hasn’t changed—AI should help people do their best work by understanding their context—but the product architecture has evolved. The shift from enterprise search to agentic systems is baked directly into the release. Glean shipped 200 new features this fiscal year, led by Glean Agents, its environment for building and governing enterprise AI agents. These agents sit on top of the updated Agentic Engine 2, which offers deeper reasoning and orchestration capabilities, and a third-generation AI assistant that acts as a front door for daily use.

It’s a long way from basic relevance ranking. Still, the company hasn’t abandoned the idea that knowledge access is the foundation. Glean reports it has indexed more than 27 billion documents since inception across over 100 SaaS connectors. That scale helps explain the demand for contextual automation—enterprises are trying to activate institutional memory in ways traditional systems never really managed.

On the ecosystem front, Glean is pushing deeper into cloud, data, and security partners. Collaborations with AWS, Google, and Microsoft anchor the big three, but the list also includes Databricks, Dell Technologies, Palo Alto Networks, Snowflake, Workday, and Zoom. For readers tracking cross-platform AI operability, this push mirrors what’s happening with providers building on top of Microsoft 365 Copilot and AWS’ agentic tooling. AWS’ AI roadmap in particular has emphasized governance layers—something reflected in its new Agentic AI Specialization—noted recently in an AWS announcement. Glean’s alignment there isn’t accidental.

Adoption metrics suggest enterprises aren’t just kicking the tires anymore. The number of company‑wide Glean deployments has more than doubled, and large contracts—$1M and above—have grown nearly threefold. That is usually the sign that AI tools have moved out of innovation teams and into the operational stack.

User behavior is also shifting. Glean reports an average of five queries per employee per day and a weekly active-to-monthly active ratio of 40 percent. For context, the company notes that’s more than twice the SaaS benchmark. It’s a small detail, but it tells you a lot about how integrated the tool has become in daily workflows. You don’t hit consumer‑search‑level interaction rates inside companies unless people feel the system actually works.

Perhaps the scale metric that stands out most is token consumption. Glean customers are generating more than 20 trillion tokens per year on the platform, with usage doubling in the past quarter. It places the company among the highest‑scale enterprise consumers of foundation models. And yet, this isn’t a story about building the biggest LLM. It’s one about orchestration, retrieval, and agentic behavior layered on top of multiple models.

That theme shows up again in the industry recognition list, which spans the CNBC Disruptor 50, Fast Company’s Most Innovative Companies, and Gartner’s recognition in Agentic AI. Awards alone don’t carry much weight for practitioners, but the consistency across both business and technical evaluators matters. It signals that Glean isn’t being pigeonholed as a search product or a point solution.

CEO Arvind Jain frames the milestone with a pointed observation: enterprises aren’t experimenting anymore, they’re operationalizing AI at scale. The next decade, he argues, won’t be defined by who builds the largest model but by who delivers trusted and useful systems on top of them. It’s a pragmatic stance. And it echoes a question many CIOs are asking quietly: how much of their AI advantage will come from model innovation versus system-level engineering? The answer appears to be shifting toward the latter.

Glean’s broader platform vision ties together Assistant, Agents, an enterprise graph, and the agentic engine—all with permissions enforcement, governance, and referenceability. The company emphasizes that it requires no costly professional services and offers LLM choice, which is quickly becoming table stakes. Even so, the breadth can be overwhelming to teams still figuring out how to layer agentic behavior into existing workflows. That’s where the partner ecosystem and connectors often do the heavy lifting.

A final note: the company is using its Glean:LIVE event on December 10 as the venue to unveil the next evolution of AI at work. We’ll see how far the roadmap pushes beyond orchestration and into autonomous execution. For now, the $200M ARR milestone is less about the number itself and more about what it signals—enterprise AI is breaking out of its pilot phase, and Glean has positioned itself as a core layer in that shift.