Glean
PaidAI-powered enterprise search and knowledge assistant. Search across all company apps, get AI-generated answers, and surface relevant information automatically.
What does this tool do?
Glean is an enterprise AI search and knowledge management platform that aggregates information across an organization's entire software stack—email, documents, project management tools, CRM systems, and more—to provide employees with AI-generated answers and contextual insights. Rather than forcing users to manually search across dozens of disconnected apps, Glean indexes all company knowledge and uses large language models to synthesize answers that pull from relevant sources across the organization. The platform comprises three core components: a semantic search engine that understands intent beyond keyword matching, an AI Assistant that answers questions with company-specific context, and Agents that can automate routine knowledge work tasks. This is purpose-built for enterprise environments where information fragmentation is a significant productivity drain.
AI analysis from Feb 23, 2026
Key Features
- Semantic enterprise search that understands intent and context rather than relying on keyword matching alone
- AI Assistant that synthesizes answers from multiple company sources and provides sources/citations for transparency
- Glean Agents for automating routine knowledge-based workflows and tasks
- Multi-source indexing supporting connections to email, documents, CRMs, project management, HR systems, and custom data sources
- Permission-aware search results that respect existing access controls across connected applications
Use Cases
- 1Sales teams quickly accessing competitive intelligence, customer history, and deal information without navigating multiple CRM and document systems
- 2Onboarding new employees by providing instant access to company policies, processes, and institutional knowledge across all platforms
- 3Support and customer success teams answering customer questions with accurate, context-aware responses drawn from internal documentation and ticket history
- 4Engineering teams finding relevant code documentation, architectural decisions, and past solutions across repositories and knowledge bases
- 5HR teams fielding policy questions and providing employees with accurate benefits, compliance, and procedural information instantly
- 6Executive teams getting synthesized business intelligence and insights from scattered reports, analytics tools, and strategic documents
Pros & Cons
Advantages
- Gartner Peer Insights recognition (4.5/5 with 103 reviews) and strong G2 rating (4.8/5 with 130+ reviews) demonstrate genuine enterprise validation and customer satisfaction
- Multi-source indexing across enterprise apps means knowledge lives in one searchable place rather than forcing users to context-switch between tools
- AI Agents provide automation capabilities for routine knowledge tasks, potentially reducing manual work beyond simple search queries
- Works across disconnected systems without requiring data migration, meaning faster deployment and lower implementation friction
Limitations
- Pricing details are not publicly available on the homepage, creating purchasing friction and making ROI analysis difficult for prospective customers
- Requires integration setup with existing enterprise tools—limited detail on how simple or complex these connections actually are in practice
- AI-generated answers depend entirely on underlying knowledge quality and comprehensiveness; if source systems have gaps or outdated information, Glean will reflect those problems
- No mention of data privacy controls, data residency options, or compliance certifications, which are critical for enterprises handling sensitive information
Pricing Details
Pricing details not publicly available.
Who is this for?
Mid-to-large enterprises (500+ employees) with fragmented technology stacks, particularly sales, customer success, HR, and engineering teams. Best suited for organizations where information lives across 10+ different applications and employees spend significant time searching for answers across disconnected systems.