Glean dominance in enterprise AI search

Workday research shows 81 percent of employees shuffle information between platforms that do not communicate. This manual coordination creates friction in the workplace. Glean solves this by connecting to over 250 workplace tools. I find Glean to be the most effective way to bridge these gaps. The company passed $300 million in annual recurring revenue in May 2026. This growth follows a June 2025 Series F round led by Wellington Management that valued the company at $7.2 billion. This follows a September 2024 Series E round where the company took $260 million at a $4.6 billion valuation. Founders Arvind Jain, T.R. Vishwanath, Piyush Prahladka, and Tony Gentilcore built the platform to solve the problem of SaaS sprawl. Jain previously co-founded Rubrik after seeing employees struggle to find information as the team grew to 1,500 people. The team includes engineers from Google, Microsoft, Meta, and Uber. Glean has received funding from investors such as Sequoia Capital, Kleiner Perkins, and SoftBank Vision Fund 2. Customers include many of the top 10 largest companies in telecommunications, banking, retail, travel, social networking, manufacturing, semiconductors, and electronics.

Understanding the knowledge model

Glean uses an enterprise knowledge graph to index content, people, and activity. This model allows the AI to understand a company’s unique internal language and collaborative relationships. The system respects real-time data permissions to ensure users only see information they have the right to access. I find the permission-aware search more reliable than general models because it uses specific company context and role-based access. Glean Assistant allows users to summarize information or create work artifacts. Glean Agents perform multi-step workplace tasks through connected systems. In September, Glean released next-generation prompting features to enable multi-step agentic reasoning. Expert detection identifies internal subject matter experts by mapping subjects to people through an understanding of company content and employee activity. In-context recommendations surface related content via a browser extension. The platform uses retrieval-augmented generation to pull relevant, up-to-date information and supports LLM options including Anthropic Claude and Google Gemini.

Because Glean relies on pre-processed indexes, users may find that content updates take hours to appear, which potentially slows down teams that require immediate access to the most current operational data. If you have a massive stack of tools, does the indexing latency affect your real-time decision making?

Implementation and market alternatives

I recommend Glean for large organizations that need to search across a complex enterprise stack. I would caution you about the testing phase during a pilot. Glean prevents prospects from connecting their own Salesforce, Slack, or Confluence systems during the evaluation period. Instead, you must test the tool within a sandbox environment. This limitation forces you to rely on trust rather than your actual data. Glean does not publish standard prices, so you must negotiate with sales teams. Vendr reports a median contract of $99,000 per year for Enterprise Flex models. You should also account for seat minimums that often reach 250 users. Buyers report renewal increases of 30 to 50 percent as usage scales. While Glean excels at search, companies that need a verified knowledge base might find Guru a better fit. Guru provides verification workflows for subject-matter experts. Companies seeking an action layer might look at Coworker, which connects to 50 plus tools and allows agents to update CRM records and draft follow-ups. For those with strict data residency mandates, Onyx provides a self-hostable option using Docker or Kubernetes. If your data lives mostly in Microsoft 365, Microsoft Copilot provides deep integration with SharePoint, OneDrive, Teams, and Outlook.