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Glean

Glean is enterprise search that respects who you are: it indexes the organisation's applications and answers questions with citations, showing each person only what their permissions allow. The knowledge sprawl across drives, wikis, tickets and chats becomes one queryable surface.

Its Work AI direction builds on that foundation: assistants and agents grounded in company knowledge, with the permission-awareness that makes enterprise deployment survivable.

It is bought at organisational scale: the indexing, connectors and governance assume hundreds of seats and a real IT function.

01FACTS
Cost
Enterprise
Ease
Model
Hosted service
Checked
August 2026

Prices, plans and model versions change fast: this is a mid-2026 snapshot; check the tool's official site for the latest.

02FIT

Best for

  • Search across the organisation's applications at once
  • Permission-aware answers that respect access rights
  • Cited answers grounded in company content
  • Assistants and agents on the same governed foundation
  • Organisations drowning in knowledge sprawl

Less suited to

Small teams are outside the shape: the connectors, indexing and governance assume enterprise scale, and the procurement matches. Below that, workspace-native AI covers most of the need.

Answer quality also inherits the estate's hygiene: stale documents produce well-cited stale answers.

03EVIDENCE

Costs & data, in short

Enterprise per-seat pricing by agreement; procurement-grade rather than credit-card SaaS.

Glean indexes your company systems with permissions preserved; its security model is the product, review it accordingly.

Plans

Published plans and prices
Glean Core SuitePrice on applicationno list price published
Glean Model Hub UsagePrice on applicationusage billed at API rates

Prices as of August 2026. Prices and plans change regularly. Check with the provider before you buy.

04IN PRACTICE

In practice

How Glean is used, area by area.

Jobs

Operations
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Glean removes the where-is-that-document tax on operations

Glean removes the where-is-that-document tax on operations. Policies, process docs and past decisions surface from wherever they live across the application estate, permissions intact, with citations attached, which cuts the interruptions that make ops teams the company's human search engine and gives every answer a source someone can check. The value tracks how messy the tool sprawl is, which is precisely the condition operations teams inherit. Scale draws the boundary: below enterprise size, workspace-native AI covers most of the need, since the connectors, indexing and governance assume hundreds of seats and a real IT function. Content hygiene also remains your job, because stale documents produce well-cited stale answers.

Example tasks

  • Find the current version of any process across systems
  • Answer operational questions with citations to the source
  • Surface who owns what from the knowledge itself
  • Cut duplicate-question load with self-serve answers
  • Audit where knowledge actually lives across the estate

Limits

Operations teams below enterprise scale get most of the value from their workspace suite's own search and AI; Glean's machinery pays off when the app estate is genuinely sprawling. Content hygiene remains your job.

Compares

vsPick Glean whenPick the other when
Notion AIGlean removes the where-is-that-document tax across the whole app estate, surfacing policies, process docs and past decisions from wherever they live with permissions intactthe team's knowledge concentrates in one workspace below enterprise scale
GuruFull comparison →Glean removes the where-is-that-document tax without asking anyone to curate first, and its value tracks how messy the sprawl is, which is precisely the condition operations inheritsthe process canon needs owners and verification states, so an answer comes from an SOP somebody still stands behind
Sana (Workday)Full comparison →Glean stops operations being the company's human search engine, cutting the duplicate-question load and surfacing who owns what from the knowledge itselfthe gap is that knowledge exists but does not reach people, and onboarding should run on learning paths personalised by role
Productivity & personal assistant
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The daily productivity problem in a large company is not writing

The daily productivity problem in a large company is not writing, it is finding: the document exists, someone has already answered the question, and neither is where you would look. Glean indexes the app estate behind connectors and answers from it, so the assistant's usefulness scales with how much of your work already lives in connected systems rather than with how well you prompt. That is the opposite trade from a general assistant, which knows a great deal about the world and nothing about your company until you paste it in.

Example tasks

  • Answer a question from material already in connected systems
  • Find the current version of a document without knowing where it lives
  • Identify who has worked on something before starting
  • Surface prior answers to a repeated internal question
  • Reach across systems in one query rather than searching each

Limits

A small team on one or two tools, where the index has little to cover and a general assistant is cheaper and simpler.

Compares

vsPick Glean whenPick the other when
Slack AIFull comparison →Glean starts from the observation that the daily problem in a large company is not writing but finding: the document exists, someone has already answered the question, and neither is where you would lookthe team thinks out loud in one workspace and a recap should compress a missed day into a minute
Microsoft CopilotFull comparison →Glean finds the current version of a document without anyone knowing where it lives and surfaces the answer someone already gave to the same internal question beforeWord, Excel, Outlook and Teams are where the day already happens and tenant permissions should decide what the assistant can see
Google GeminiFull comparison →Glean identifies who has worked on something before you start, which is a question no amount of drafting capability answersthe working day sits inside Google Workspace and the assistant should be in the same place

Tasks

Search & knowledge retrieval
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Glean is enterprise search done as a product rather than a feature

Glean is enterprise search done as a product rather than a feature. It indexes the whole tool sprawl (Drive, Slack, Jira, wikis, tickets) and answers questions from all of it at once, with each person seeing only what their permissions allow, which is the feature that makes enterprise deployment survivable and the price justifiable. Assistants and agents build on the same governed foundation. It is bought by organisations drowning in their own knowledge, at a scale where the answer exists somewhere and nobody can find it. The shape excludes the rest: small teams get most of the value from workspace-native AI, citation-first web research and personal corpus tools solve different problems, and answer quality inherits the estate's hygiene.

Example tasks

  • Search every connected system from one box
  • Get cited answers that respect permissions
  • Find the decision, the document and the person together
  • Ground assistants in governed company knowledge
  • Onboard new joiners onto the organisation's actual knowledge

Limits

Citation-first web research and personal knowledge tools solve different problems; Glean is specifically the enterprise's internal estate. Permission-awareness is the feature that justifies the price, and only enterprises need it.

Compares

vsPick Glean whenPick the other when
Microsoft CopilotFull comparison →Glean turns knowledge sprawled across applications beyond any single suite, drives, wikis, tickets and chats, into one governed, cited search surface with permissions respectedthe knowledge already lives in the Microsoft estate, in email, chats, meetings and files
GuruFull comparison →Glean indexes the whole tool sprawl and answers from all of it at once, so the answer that exists somewhere becomes findable without anyone curating it firstretrieval is a trust problem rather than a reach problem, and the answer exists in several versions with nobody sure which to believe
Sana (Workday)Full comparison →Glean returns the decision, the document and the person together, so a new joiner is onboarded onto what the organisation actually knows rather than what someone wrote down for themthe agents should act as well as answer, and a learning platform grows from the same foundation
Gemini NotebookFull comparison →Glean's permission-awareness is the feature that justifies the price, and it lets assistants and agents build on the same governed foundation rather than each getting its own accessthe work is per-corpus and personal, a defined set of documents rather than the whole estate
PerplexityFull comparison →Glean is specifically the enterprise's internal estate, which is a different problem from citation-first web research rather than a weaker version of itthe question is about the world outside the company and the answer should arrive with numbered public sources
Slack AIFull comparison →Glean indexes Slack as one source among Drive, Jira, wikis and tickets, so an answer assembled from two systems at once is possiblethe working conversation is the corpus and the team thinks out loud there
Google GeminiFull comparison →Glean searches every connected system from one box, which is the shape of the problem when the answer exists somewhere and nobody can find itthe answers need to draw on the live web and your own Google Workspace at once
06FAQ

Common questions

Is Glean free?

No: Glean is enterprise software, priced per organisation.

Where does Glean fit best?

Glean fits best in Operations and Productivity & personal assistant; see its practice notes for how.

Before sharing confidential or personal data, check this tool's data-governance and training policies. They differ between providers and can change.

Last checked: August 2026

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