Glean

Glean is an enterprise AI search and knowledge management platform. Think of it as Google Search for everything inside your company. It connects to all the applications your organisation uses — Slack, Microsoft Teams, Google Workspace, Confluence, Jira, Salesforce, GitHub, SharePoint, email, and over 100 other enterprise apps — and gives every employee a single, intelligent place to find any company information. Instead of opening five different apps and running separate searches in each one, an employee types their question into Glean (in plain English) and receives results from all connected sources simultaneously, ranked by relevance. Beyond search, Glean's AI assistant can answer questions directly — reading the relevant content and providing a clear, sourced response rather than just a list of documents to wade through. Glean also includes people search (finding the right internal expert), knowledge discovery (surfacing information employees did not know existed), and Glean Agents (AI that can complete tasks across connected applications, not just find information).

Arvind Jain is the Founder and CEO of Glean Technologies. His background is exceptionally well-matched to building enterprise AI search. He spent over 10 years at Google, where he led engineering teams across three of the company's most important products: Google Search (where he worked on the infrastructure and algorithms that power the world's most-used website), Google Maps (contributing to the data and search systems that help billions navigate), and YouTube (working on the recommendation and search systems that help users discover content). This decade of experience building search and data products at the world's best search company gave Arvind a world-class understanding of how to build search that genuinely works. After Google, Arvind co-founded Rubrik — a cloud data management company that became one of Silicon Valley's fastest-growing enterprise software companies, eventually going public. Rubrik's success demonstrated Arvind's ability to build and scale enterprise products that large organisations actually adopt. With Glean, Arvind set out to solve what he saw as one of the most significant and underserved productivity problems in the enterprise: the daily struggle of employees to find information across an ever-growing number of applications and data sources.

Regular search engines like Google search the public internet — content that is available to everyone. Enterprise search tools like Glean search your company's private, internal content — the information that only your organisation's employees can access. But the differences go deeper than just what content is searched. Glean's search understands the meaning behind queries (not just keyword matches) — so "the Q4 sales deck" and "the fourth quarter presentation" return the same results. Glean's results are personalised to each employee — a software engineer and a sales rep searching for "the product roadmap" see different results because they need different versions. Glean respects security permissions — employees only see content they are already authorised to access. Glean searches across all your applications simultaneously — not just one source at a time. And Glean's AI can synthesise information from multiple sources into a direct answer, rather than just listing documents to click through. Traditional enterprise search tools (like SharePoint search or Confluence search) search only within a single application, use keyword matching rather than semantic understanding, and do not provide AI-generated answers. Glean is a fundamentally different product from these tools.

Security is a core architectural feature of Glean, not an afterthought. The most important security feature is permission-aware search: Glean integrates with each connected application's existing security and access control systems. When an employee searches Glean, the results they see only include content they are already authorised to access in the underlying applications — if an employee does not have permission to see a particular document in Google Drive, they will not see it in Glean either. Data is encrypted in transit and at rest. Glean's AI-generated answers are also generated only from content the searching employee can access — the AI cannot synthesise a summary that reveals information from restricted documents. Glean maintains SOC 2 Type II security certification and meets the requirements of enterprise security standards including GDPR compliance for European operations. Each organisation's data in Glean is isolated from other organisations' data. Companies can also configure Glean to exclude particularly sensitive content types or applications from indexing. Despite these protections, each organisation deploying Glean should conduct its own security evaluation and ensure the platform meets its specific data handling requirements and compliance obligations.

Glean integrates with over 100 enterprise applications out of the box. Key integrations include communication platforms: Slack, Microsoft Teams, Google Chat. Document and file storage: Google Drive, SharePoint, OneDrive, Dropbox, Box. Knowledge management: Confluence, Notion, Guru, SharePoint Pages. Project management: Jira, Asana, Monday.com, Linear, GitHub. CRM: Salesforce, HubSpot. Customer support: Zendesk, Intercom, ServiceNow. HR: Workday, BambooHR. Code repositories: GitHub, GitLab, Bitbucket. Email: Gmail, Outlook. Video conferencing and recordings: Zoom, Google Meet. And many more specialised enterprise applications. The integration library continues to expand with each Glean update. Each integration is engineered to connect to the specific API of that application, handle its authentication requirements, respect its permission model, and index its content in a way that makes it searchable alongside content from all other connected applications — a non-trivial technical challenge at scale.

Glean and Microsoft Copilot are both enterprise AI platforms with overlapping capabilities, but they differ in important ways. Microsoft Copilot for Microsoft 365 is embedded within Microsoft's own products — Word, Excel, PowerPoint, Teams, Outlook — and primarily helps users work within these Microsoft applications. Its search capabilities are strongest within the Microsoft 365 ecosystem (SharePoint, OneDrive, Teams, Exchange). Glean, by contrast, is application-agnostic: it connects to the full range of enterprise applications a company uses, including Slack, Salesforce, Jira, GitHub, and many others that are not part of the Microsoft ecosystem. Organisations that use a mix of Microsoft and non-Microsoft applications typically find Glean more comprehensive for cross-application search and knowledge discovery. Microsoft Copilot's significant advantage is distribution: it is available to the hundreds of millions of existing Microsoft 365 subscribers at low incremental cost. Glean's advantage is depth and breadth of non-Microsoft application integration and its specialised focus on search quality and knowledge discovery. In practice, many organisations use both tools — Copilot for work within Microsoft applications, and Glean for cross-application search and knowledge discovery.

Glean is primarily designed for large enterprises — typically organisations with hundreds or thousands of employees and complex information environments spread across many different tools. The value proposition is strongest when there are enough employees, enough applications, and enough information volume that finding things is genuinely difficult and time-consuming. For small businesses with 10-50 employees using only a few tools, the information landscape is simpler and the ROI from a sophisticated enterprise search platform is less compelling. Small businesses typically find that built-in search features in individual applications, combined with good information hygiene (consistent naming, clear organisation), are sufficient for their needs. Glean's pricing and implementation requirements are also typically calibrated for enterprise deployments rather than small business use. If you are a small business, simpler knowledge management tools (like Notion, a well-organised Google Drive, or Slack's own search) may be a more proportionate solution. If your organisation has hundreds of employees, multiple teams, and a complex stack of applications, Glean is worth evaluating seriously.

Implementing Glean at enterprise scale involves several phases. The initial technical setup — connecting Glean to the organisation's most important applications and configuring basic security settings — typically takes 2-4 weeks. This involves IT teams authorising each application integration, configuring Glean's access to the relevant data, and initial indexing of existing content. After the initial setup, there is typically a period of configuration and refinement — adjusting which content sources are prioritised, configuring the AI assistant's knowledge, setting up any custom workflows, and ensuring the search results quality is good for the organisation's specific terminology and content. Full deployment to all employees, including change management (communicating the new tool to employees, training, and driving adoption) typically takes 1-3 months from initial setup to broad active use. The total time investment for a successful enterprise deployment is significant, but Glean has a customer success team that guides organisations through the implementation process and has established best practices based on hundreds of enterprise deployments. Most organisations report that the productivity benefits are visible and measurable within the first few months of deployment.

Glean Agents represent the next evolution in Glean's platform — moving from AI that finds and answers questions to AI that takes actions and completes tasks. Where Glean's search and AI assistant help employees find information and get answers, Glean Agents can be given a task and complete it autonomously, using Glean's connections to all enterprise applications. Examples of tasks a Glean Agent might complete: "Summarise all customer support tickets opened in the last 48 hours, categorise them by issue type, and draft a status update for the team" — the Agent reads the tickets from the support system, analyses them, and produces the summary and draft. "Find all open invoices from supplier X that are more than 30 days overdue and list them with relevant contact information" — the Agent searches the finance and procurement systems and compiles the list. "Review the product feedback from the last month in Slack and Jira and identify the five most frequently requested features" — the Agent reads across Slack conversations and Jira tickets and synthesises the analysis. Agents can complete multi-step tasks that require gathering information from multiple sources and synthesising it into a result, with humans reviewing the output before it is acted upon. This is a rapidly developing area of Glean's platform with new capabilities being added regularly.

The future of enterprise AI search is moving rapidly from "helping employees find information" to "helping employees act on information" — a shift from passive retrieval to active assistance. In the near term, improvements in AI models will make search and AI answers significantly more accurate, better at handling complex multi-part questions, and more effective at understanding company-specific terminology and context. Personalisation will deepen — AI assistants will learn individual employees' working styles, preferred information sources, and most common information needs, proactively surfacing relevant information rather than waiting to be asked. The integration of search with workflow — where finding information automatically triggers the next step in a process rather than the employee having to take that step manually — will become more common. AI agents that can complete multi-step information tasks autonomously will become a standard part of the enterprise knowledge worker's toolkit. Longer term, the distinction between "finding information" and "completing work" will blur: AI assistants will handle not just the search but much of the information processing, synthesis, and communication that follows the search, leaving human workers to focus on judgment, creativity, and relationship-building. Glean is actively building toward this future with its AI assistant and Agents capabilities.