Glean

What is Glean

Glean is an enterprise AI platform founded in 2019 by former Google search engineers, including CEO Arvind Jain. Originally built as an enterprise search tool that could find anything across a company's fragmented knowledge stack, Glean has evolved into a comprehensive work AI platform that combines unified search, a generative AI assistant, and the ability to build custom AI agents grounded in the organization's data. It has become the standard "work AI" choice for many mid-market and enterprise companies that want AI that actually knows their business.

Glean works by connecting to the apps and systems where company knowledge actually lives — Google Workspace, Microsoft 365, Slack, Notion, Confluence, Jira, Salesforce, Zendesk, GitHub, Box, Dropbox, ServiceNow, Workday, and dozens of others. It builds a unified, permissions-aware index of this content, then provides search and AI experiences on top. When an employee asks the Glean assistant a question, it retrieves relevant context from every system they have access to and produces an answer with citations back to the original sources.

The platform's positioning is enterprise-first. Glean has invested heavily in the requirements that matter to large companies: respecting source-system permissions so users only see what they're allowed to see, comprehensive audit logging, SSO and identity integration, deployment in customer-controlled cloud environments, and the operational maturity to support tens of thousands of users in a single deployment. This focus has made Glean one of the fastest-growing enterprise software companies of the past several years.

Key features

• Unified Enterprise Search — Search across every connected app from a single interface, with permissions enforced from the source system
• Glean Assistant — Generative AI assistant grounded in the company's actual data, with citations to source documents
• Custom Agents — Build no-code AI agents for specific workflows (onboarding, sales prep, support triage, engineering on-call)
• Connectors for 100+ Apps — Pre-built integrations to Google Workspace, Microsoft 365, Slack, Notion, Confluence, Salesforce, and many others
• Knowledge Graph — A continuously updated graph of people, content, and relationships derived from all connected sources
• In-App Search — Embedded search experiences inside Slack, browser extensions, and a desktop app
• Generative APIs — Build AI experiences on top of the Glean knowledge platform via API
• Trust & Permissions — Source-system permissions are enforced at query time, so search never reveals content a user shouldn't see
• Analytics & Insights — Dashboards showing how knowledge is created, consumed, and where gaps exist

Pros

✅ The breadth of pre-built connectors is the strongest in the category — onboarding to a new app is usually a configuration step, not an engineering project

✅ Source-system permission enforcement is genuinely well-implemented, addressing the biggest fear enterprises have about deploying AI on internal data

✅ The Assistant's grounding in retrieved company knowledge produces answers that are far more useful than a generic LLM applied to the same questions

✅ Custom Agents allow non-engineering teams to build their own AI workflows without IT bottlenecks

✅ Glean's operational maturity — uptime, support, security certifications — is unusual for an AI-first product, making it credible at enterprise scale

Cons

⛔️ Pricing is enterprise-tier — Glean is not realistically accessible for small businesses or solo users

⛔️ The initial deployment and connector configuration is a real project requiring IT investment, not a self-serve experience

⛔️ Output quality depends entirely on the quality of the underlying content — Glean can't make scattered, contradictory company knowledge consistent

⛔️ Some niche applications and custom internal tools lack pre-built connectors, requiring custom integration work

⛔️ Competitive landscape is intensifying as Microsoft Copilot, Google Workspace AI, and others expand into the same space

Who is using Glean

Glean has built a notable customer base in mid-market and enterprise companies that have outgrown their internal search and want AI grounded in their own data:

• Tech companies including Pinterest, Confluent, Databricks, Duolingo, Reddit, Sony, and Workday have publicly used Glean
• Enterprises in regulated industries — banks, insurers, healthcare organizations — that need careful permissions handling
• Customer-facing teams (sales, support, customer success) using custom agents to retrieve account context and prep materials
• Engineering organizations using Glean as a unified search across code, docs, runbooks, and tickets
• HR and people operations teams using Glean for policy lookup, onboarding, and internal knowledge access
• IT and operations teams deploying Glean as the front door to a sprawl of internal tools

Glean's customer logo wall includes a meaningful share of the most recognizable technology and Fortune 500 companies, and its customer count has grown rapidly through 2024 and 2025.

Pricing

Disclaimer: Glean does not publish public pricing. Costs vary significantly by company size, connector count, and deployment options. For accurate quotes, contact Glean directly.

What makes Glean unique?

Glean's defining advantage is the combination of breadth, depth, and trust. The breadth comes from 100+ connectors — Glean indexes more of the typical enterprise knowledge surface than any competitor, including app categories (HR systems, ITSM, CRM, code repositories) that many AI tools ignore. The depth comes from the AI layer being purpose-built on top of that index rather than bolted on — every Assistant response is grounded in real retrieved content with citations, not generic LLM output.

The trust layer is what makes Glean credible to enterprise IT and security teams. Source-system permissions are enforced at query time, so a Glean search for an employee never reveals content the source system wouldn't have shown them directly. This sounds basic but is technically hard to do correctly across heterogeneous permission models, and Glean has invested years in getting it right.

The custom agent capability is the more recent strategic move. By letting customers build their own agents for specific workflows — sales call prep, customer support triage, engineering on-call, onboarding — Glean shifts from being a search tool to being the platform on which a company's AI-augmented work runs. This positions it competitively against horizontal AI tools that lack the enterprise integration depth.

How I rate it

Final thoughts

Glean has become the default enterprise AI platform for companies serious about deploying AI on top of their actual organizational knowledge. The combination of broad connector coverage, robust permissions enforcement, grounded Assistant responses, and custom agent capability addresses the requirements enterprise IT teams care most about — and few competitors match the full breadth.

The product is not for everyone. Pricing, deployment effort, and the assumption that the customer has a meaningful number of connected SaaS apps make Glean a poor fit for small businesses or solo users — those audiences are better served by ChatGPT Team, Claude for Teams, or Microsoft Copilot. But for any company with hundreds or thousands of employees, a sprawl of work apps, and a need to make organizational knowledge accessible through AI, Glean is the clear front-runner in 2026. If you're scoping enterprise work AI, Glean should be on the evaluation list — and often comes out on top of it.