Sacra estimates Glean hit $208M in annual recurring revenue (ARR) in 2025, up 89% year-over-year from $110M in 2024.

Glean generates revenue primarily through enterprise software subscriptions, with pricing based on number of seats/users within an organization. The company focuses on mid-market and enterprise customers with 500+ employees, with typical initial contract values ranging from $100K to $500K annually.

Enterprise deals with Fortune 500 companies can exceed $5M annually.

The company initially targeted technology companies with 500-2,000 employees but has successfully moved upmarket to serve large enterprises across industries including financial services, telecommunications, and healthcare. Key reference customers include Databricks, Canva, Confluent, Duolingo, and T-Mobile. Sales cycles average 4-5 months for enterprise deals, with faster 90-day cycles for mid-market customers under 1,000 employees.

Glean was valued at $7.2B during its $150M Series F led by Wellington Management in June 2025, up from $4.6B at its $200M Series D led by Kleiner Perkins in September 2024.

That followed a $100M Series C in May 2023 at a $1B valuation, backed by Sequoia and General Catalyst.

Since its founding in 2019, Glean has raised roughly $768M, with backers including Sequoia, Kleiner Perkins, Lightspeed, ICONIQ, General Catalyst, and Wellington.

Glean was founded in 2019 by Arvind Jain, a distinguished engineer from Google Search, along with several other ex-Google engineers. The founding team identified a critical problem while working at Rubrik (Jain's previous startup): as companies scaled rapidly, employees struggled to find information scattered across numerous SaaS applications, leading to significant productivity losses.

Glean found product-market fit as an AI-powered enterprise search platform for mid-market technology companies with 500–2,000 employees. These companies were large enough to experience acute information discovery problems but agile enough to quickly adopt new tools. Initial customers included fast-growing tech companies like Databricks, Canva, and Confluent.

The product functions as a unified search and execution layer across all enterprise applications, including Slack, Google Workspace, Microsoft 365, Salesforce, Jira, and others. When employees have questions, they can use Glean's chat interface to find relevant information from any connected system, with results filtered based on their specific permissions and role.

Glean has repositioned itself as an enterprise AI middleware layer designed to sit between large language models and internal company systems. It provides three core components: abstraction across multiple model providers; deep integrations that map and retrieve enterprise information via a proprietary Enterprise Graph; and a permissions-aware governance layer that prevents data leakage while surfacing citations back to source documents.

The Glean Agents platform and Glean Assistant together form the company's current agentic product surface. Glean Agents offers 30+ prebuilt agents, per-step model selection, and a model hub spanning Amazon Bedrock, Google Vertex AI, and Azure OpenAI. The third-generation Glean Assistant adds fast and extended thinking modes, deep research, scheduled agents, and agent version control, and now supports 100+ native actions across connected apps, real-time voice and slide generation (beta), and agent sandboxes (forthcoming). Users engage with the Assistant six times per active day on average, and Glean Agents powers over 100 million agent actions annually at a run rate exceeding 20 trillion tokens per year.

Glean is an enterprise SaaS company targeting mid-market and enterprise companies with 500+ employees. Revenue is generated through per-seat subscription licensing, with contracts typically starting north of $100K annually for mid-market deployments and reaching multi-million dollars for large enterprises.

Glean is available on both the AWS Marketplace AI Agents and Tools category and Microsoft Azure Marketplace, enabling procurement through existing cloud spend commitments and broadening access to enterprise buyers.

The core product connects to and indexes content across all enterprise systems (Salesforce, ServiceNow, Google Workspace, etc.) to create a unified search and agentic execution layer.

Glean's key technical differentiator is its permissions-aware governance model—ensuring users only see content they're authorized to access while maintaining security compliance. Hundreds of pre-built connectors create a structural advantage against new entrants.

Glean employs a land-and-expand strategy, typically starting in specific departments (often engineering or customer support) before expanding company-wide. The company has demonstrated strong expansion metrics, with examples of $60K initial lands growing to $500K+ contracts within nine months. Sales targets CIOs and CTOs, with typical enterprise sales cycles of 4–5 months.

Glean operates in the enterprise search and knowledge management market, which includes both established players offering traditional enterprise search solutions and newer AI-powered workplace assistants.

The traditional enterprise search segment includes long-standing solutions like Microsoft SharePoint Search, Elastic Enterprise Search, and Coveo. These platforms focus primarily on indexing and searching internal company documents and data sources. While they offer robust security controls and integration capabilities, they generally lack sophisticated AI-powered features and natural language understanding. Many require significant IT resources to implement and maintain. More recently, hyperscalers have moved to bundle enterprise search directly into their broader cloud and productivity offerings: Amazon has rolled out Quick Suite (fusing Q for Business with its analytics product) and Google has expanded Gemini Enterprise with Agentspace, with both positioning against Glean by targeting broad employee adoption.

This newer category includes companies like You.com Enterprise, Moveworks, and Guru, which leverage large language models to provide more intuitive search experiences. You.com Enterprise focuses on providing a ChatGPT-like interface for company knowledge, while Moveworks specializes in IT support automation. Guru takes a different approach by focusing on knowledge verification and management through browser extensions and Slack integrations.

A third category includes comprehensive knowledge management platforms like Notion, Confluence, and Microsoft Viva Topics, which combine document management, collaboration tools, and search but often struggle to synthesize information across disparate enterprise systems.

Glean's response to incumbent pressure has been active ecosystem participation rather than neutrality: it is a Microsoft 365 Agent launch partner and is generally available on both Microsoft Azure Marketplace and AWS Marketplace, positioning it as a complement to—rather than a replacement for—incumbent productivity suites. This reduces the risk of Microsoft or AWS treating Glean as a hostile third-party tool while also giving Glean access to their enterprise procurement channels.

Glean has tailwinds from the rapid proliferation of enterprise SaaS applications and the growing demand for AI-powered workplace tools, with opportunities to expand into adjacent markets like enterprise knowledge management, workflow automation, and intelligent workplace assistants.

The core enterprise search market that Glean currently serves is significant, but represents just a fraction of their total opportunity.

As organizations increasingly struggle with fragmented knowledge across hundreds of SaaS applications, Glean's ability to unify and make this information accessible positions them to expand into broader knowledge management.

Their deep integrations with enterprise systems and sophisticated permissions management create strong barriers to entry, while their AI capabilities enable them to move beyond simple search into areas like automated documentation, knowledge base creation, and institutional memory preservation.

Glean's evolution from search tool to AI-powered workplace assistant represents their largest growth vector.

Their unique position - having access to and understanding of enterprise data across systems - enables them to build increasingly sophisticated AI assistants that can handle complex workplace tasks.

Beyond just finding information, Glean could expand into meeting summarization, email management, project tracking, and automated workflow creation. This positions them to capture share in the emerging enterprise AI assistant market, estimated to reach $40B+ by 2027.

Glean's deep understanding of how information flows through organizations positions them to expand into workflow automation and process intelligence. By analyzing patterns in how employees search for and use information, Glean can identify bottlenecks and inefficiencies in business processes.

This creates opportunities to automate routine tasks, streamline workflows, and provide insights to improve organizational productivity. The workflow automation market alone is projected to reach $78B by 2030.

Enterprise AI Fatigue & Churn: Glean's CEO acknowledges churn from "experimental AI budgets" as companies grow more demanding about proving concrete ROI. Complex 4–5 month deployments and multi-system integrations heighten the risk of failed rollouts that suppress renewal rates.

Model Commoditization: Glean's value proposition as a neutral middleware layer depends on LLMs remaining differentiated enough that enterprises want an abstraction layer across providers. If foundation models converge on price and capability, the middleware layer loses strategic necessity and Glean faces margin compression from both hyperscalers and commodity model providers.

Data Privacy/Security Concerns: Glean requires broad access to index enterprise data while routing queries through third-party LLMs, creating exposure to data leakage incidents similar to Samsung's code leak to ChatGPT. A high-profile breach involving a Glean customer could trigger enterprise-wide bans and slow adoption across regulated industries.