Who are Glean?

If you work in IT, knowledge management, or enterprise productivity, chances are you've been hearing a lot about Glean. And if you haven't yet, you will. Founded in 2019 by former Google engineers Arvind Jain and T.R. Vishwanath in Palo Alto, California, Glean has grown with remarkable speed from a smart enterprise search tool into one of the most talked-about Work AI platforms on the market. With a valuation of $7.2 billion as of June 2025 and annual recurring revenue that doubled to $200 million in just nine months, Glean has clearly struck a nerve.

The core problem Glean was built to solve is one that anyone who has worked in a large organisation will immediately recognise: company knowledge is scattered everywhere. It lives in Slack channels, Google Drive folders, Confluence wikis, Jira tickets, Salesforce records, emails, and dozens of other tools that rarely talk to each other. Employees waste hours every week searching for information they know exists somewhere but simply cannot find. Glean's answer is a unified AI platform that connects to all of those systems, understands who you are and what you're working on, and gives you intelligent answers rather than a list of links.

What started as enterprise search has evolved into something more ambitious. In 2025, Glean expanded significantly into AI agents and assistant capabilities, positioning itself not just as a search layer but as the connective tissue between AI models and enterprise systems. As CEO Arvind Jain has described it, Glean aims to be the intelligence layer that sits beneath the interface - the platform that makes generic large language models actually useful for your specific organisation.

What Does Glean Do?

Glean's platform is built around three core pillars: enterprise search, an AI assistant, and AI agents.

Enterprise Search is where Glean began and remains its most mature capability. The platform connects to over 100 enterprise applications - including Google Workspace, Microsoft 365, Slack, Confluence, Jira, Salesforce, ServiceNow, GitHub, Zendesk, and Box - and indexes their content in a permissions-aware manner. That last point matters enormously. Glean doesn't just search across your tools; it respects the access controls already in place. If a document is restricted to the finance team, it won't appear in search results for people outside that team. This permissions enforcement is fundamental to making enterprise AI trustworthy rather than a security risk.

The search itself goes far beyond keyword matching. Glean uses deep learning and what the company calls an Enterprise Graph - a model of your organisation's people, content, and relationships - to deliver personalised, contextually relevant results. When you search for something, Glean doesn't just look for documents that match your words; it understands who you are, what projects you're working on, who your colleagues are, and surfaces results that reflect your specific context.

Glean Assistant is the AI chat interface built on top of this knowledge foundation. Rather than a generic chatbot that might hallucinate answers drawn from public internet data, Glean's assistant is grounded in your company's actual information. It can answer questions, summarise documents, draft communications, and synthesise information across multiple sources - all while citing the specific internal documents it's drawing from, so users can verify the answers. Glean runs a mix of leading large language models including models from OpenAI, Anthropic, and Google, treating these providers as partners rather than positioning itself as a competitor to any of them.

Glean Agents is the newest and perhaps most strategically significant addition to the platform. Launched in general availability in May 2025 and reaching its second generation by late 2025, Glean Agents allows organisations to build and deploy AI agents that automate workflows using natural language instructions. Rather than requiring developers to write complex automation code, employees can describe what they want an agent to do and have it execute tasks across connected systems. By December 2025, Glean customers were consuming more than 20 trillion tokens annually on the platform, indicating how deeply these capabilities have become embedded in daily work.

The platform also includes Glean Protect, a governance layer that maintains security and compliance throughout all AI interactions. This is particularly important for enterprise deployments where data sovereignty, audit trails, and access controls are non-negotiable. Glean has indexed more than 27 billion documents since its founding, all handled in a permissions-sensitive manner.

Who Uses Glean?

Glean is firmly positioned as an enterprise platform. Pricing starts at roughly $50 per user per month with minimum annual contracts reportedly around $60,000, which places it squarely in the mid-to-large enterprise segment. The company has expanded its customer base significantly across North America, Europe, and Asia-Pacific.

The platform has broad horizontal appeal because knowledge fragmentation is a universal problem. Glean's customers span technology companies, financial services, professional services, healthcare, retail, and manufacturing. The platform is particularly well-suited to organisations with large knowledge worker populations - anyone where employees spend significant time searching for information, onboarding new colleagues, or trying to stay current across many systems.

Typical champions within organisations include Chief Information Officers, IT leaders overseeing the enterprise application stack, Chief Knowledge Officers or heads of internal communications, HR and L&D teams focused on employee productivity and onboarding, and increasingly, heads of AI transformation who are looking for a trustworthy, governed way to bring generative AI capabilities to their workforce.

Engineering and technical teams have also been strong adopters, with Glean providing code intelligence capabilities that allow developers to search across repositories, documentation, and internal technical resources simultaneously.

The company reached $100 million in ARR in February 2025 and doubled to $200 million by December 2025(!), making it one of the fastest-growing pure-play enterprise software companies in recent memory. This growth reflects both the breadth of the opportunity and strong retention among existing customers.

Glean Competitors

The enterprise search and Work AI market has become increasingly competitive, attracting both established technology giants and well-funded startups. Understanding where Glean sits relative to its competitors is essential for any organisation evaluating this space.

Microsoft Copilot is perhaps the most formidable competitive dynamic Glean faces. For organisations deeply invested in Microsoft 365, Copilot integrates directly into Word, Excel, Teams, Outlook, and SharePoint with native access to all Microsoft content. The key distinction is that Copilot is primarily an ecosystem play - it excels within the Microsoft universe but has more limited reach into non-Microsoft tools. Glean's strength is precisely its multi-vendor, heterogeneous environment coverage. Organisations running a mix of Google Workspace, Salesforce, Atlassian, Slack, and dozens of other tools will find Glean's cross-platform indexing more comprehensive.

Coveo is an enterprise-grade AI relevance platform with deep capabilities in personalised search, particularly for customer-facing applications such as customer support portals, e-commerce, and digital experience platforms. Coveo's AI is strong on predictive recommendations and relevance tuning, with particularly deep penetration in retail and financial services. It competes with Glean in the internal knowledge management space but has historically been stronger in customer-facing search scenarios.

Elastic occupies a different position - more of an infrastructure and developer tooling play than an out-of-the-box enterprise experience. Elastic's open-source Elasticsearch technology underlies many search implementations and provides extensive customisation and flexibility. However, it requires significant technical expertise to implement and maintain. For organisations with strong engineering teams that want to build bespoke search experiences, Elastic is compelling. For those wanting a turnkey, business-user-facing solution, Glean is considerably easier to deploy.

Guru focuses specifically on knowledge management and verified content. Rather than indexing everything across all systems, Guru enables teams to create, curate, and verify "knowledge cards" that are surfaced in context within tools like Slack and Teams. Guru's strength is structured knowledge creation and maintenance; Glean's strength is intelligent search across unstructured information that already exists. They address overlapping but distinct problems.

GoSearch and similar newer entrants position themselves as more affordable, more flexible alternatives to Glean, often highlighting concerns about Glean's pricing, minimum contract sizes, and what some customers describe as a slower deployment process. These alternatives typically offer hybrid search architectures and more flexible LLM configurations, appealing to mid-market organisations that find Glean's enterprise-scale positioning and pricing a barrier.

Moveworks competes in the AI agent and employee support space, with a particular focus on IT service management automation. Where Glean is broad and horizontal, Moveworks has traditionally gone deeper on specific use cases like IT helpdesk automation. As both companies expand their capabilities, this overlap is increasing.

What Makes Glean Different?

In a market where seemingly every vendor now claims AI-powered search, several factors genuinely distinguish Glean's approach.

The Enterprise Graph is Glean's most significant architectural differentiator. Rather than treating search as a simple document retrieval problem, Glean builds a deep model of how your organisation actually works - who works with whom, what projects are active, how information flows between teams, and what context surrounds any given piece of content. This graph is what enables personalisation that goes beyond basic role-based filtering. When a product manager searches for something, they get different results than an engineer searching for the same words, because Glean understands the different context each person brings.

Permissions-first architecture sounds like a technical detail, but it's actually a fundamental commercial differentiator. Many organisations have been reluctant to adopt AI tools because of legitimate concerns about surfacing confidential information to people who shouldn't see it. Glean's architecture enforces existing access controls at the retrieval layer, not as an afterthought. This makes it possible to deploy the platform broadly without requiring extensive remapping of security policies.

Model agnosticism is increasingly important as the AI landscape evolves rapidly. Glean doesn't bet on a single large language model provider. Instead, it acts as an abstraction layer that allows organisations to leverage whichever models best suit their needs - whether that's models from OpenAI, Anthropic, Google, or open-source alternatives - without rebuilding their search and knowledge infrastructure. As Jain has noted, this means Glean's product actually improves as frontier AI providers innovate, rather than being locked into one trajectory.

Speed of deployment and adoption has been a consistent theme in Glean customer feedback. Enterprise software implementations are notorious for going over time and budget, and AI deployments add additional complexity. Glean has invested in reducing deployment friction, with some customers reporting being live within three weeks. This matters because an AI assistant nobody uses is worthless - getting to adoption quickly is itself a form of competitive advantage.

Breadth of integration is simply difficult to replicate quickly. Glean's 100-plus connectors represent years of integration work and ongoing maintenance. Competitors often support fewer applications or require custom integration work for common enterprise tools. For organisations with complex, heterogeneous application environments, this breadth significantly reduces the effort required to get comprehensive coverage.

Momentum and investment are also relevant factors. Glean's growth trajectory - from $100 million to $200 million ARR in nine months, a $7.2 billion valuation, recognition from Fast Company, CNBC, and Gartner - signals a company with genuine commercial traction rather than just an interesting technical concept. In enterprise software, this matters: organisations investing in a platform want confidence that the vendor will be well-resourced and innovative for years to come.

Glean - Our Viewpoint

Glean has identified a genuinely important problem and built a credible solution to it. The knowledge fragmentation challenge that Glean addresses is real, pervasive, and getting worse as organisations adopt more and more SaaS tools. The fact that the company has achieved the revenue growth it has while serving genuinely large enterprises suggests the product is delivering real value, not just generating pilot interest.

Glean is clearly positioned for larger organisations and priced accordingly. The minimum contract thresholds and per-seat pricing mean this isn't a solution for small or mid-market businesses without meaningful technology budgets. For organisations in that category, lighter-weight alternatives like Guru, GoSearch, or even well-configured Microsoft Copilot may deliver sufficient value at more accessible price points.

The competitive dynamic with Microsoft is also worth watching carefully. For organisations heavily invested in Microsoft 365, Copilot's native integration and bundling within existing Microsoft agreements will be attractive, even if Glean's technical capabilities are broader. Organisations should be honest about how much of their knowledge actually lives in Microsoft systems versus elsewhere - if the answer is "mostly Microsoft," the calculus changes.

Overall, Glean represents one of the more thoughtful approaches to enterprise AI that we've seen - grounded in a genuine user problem, architecturally sound, and demonstrating real commercial momentum. For large enterprises with complex, multi-vendor application environments and the budget to invest seriously in employee productivity, it's a platform worth serious consideration.

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At Viewpoint Analysis, we help organisations cut through the noise of the enterprise technology market and run structured vendor selection processes when teams need to move quickly and confidently. If you're evaluating Work AI platforms like Glean, or trying to understand which solution best fits your organisation's specific environment and requirements, we'd be happy to help.

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