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Report: Is Glean Good or Just Hype?

18 min read
11/20/2025
Regenerate

Overview

This report looks at whether Glean (the Work AI / enterprise search and agent platform from Glean Technologies, not the unrelated Glean.ai AP automation product) is genuinely useful or mostly hype.

It focuses on three concrete promise areas taken from Glean’s own marketing and surrounding commentary:

  1. Search & productivity – does it materially improve knowledge discovery and knowledge‑worker productivity vs. traditional enterprise search?
  2. Security & compliance – does it live up to its messaging around zero‑trust architecture, permission‑aware AI, SOC 2, and enterprise governance?
  3. Deployment & operations – is it actually easy to deploy, integrate, and maintain with fast time‑to‑value in real enterprises?

Throughout, "Glean" refers to the Glean Work AI / enterprise search service unless explicitly noted as Glean.ai (the finance tool).

1. Search & Productivity: Real Gains vs. Marketing Hype

1.1 What Glean promises

Glean markets itself as a “Work AI” platform that:

  • Connects and understands all your enterprise data to give trusted answers and automate work across apps.1
  • Provides AI enterprise search and knowledge discovery with semantic understanding, generative answers, and personalized relevance.2
  • Claims customer outcomes like faster onboarding, fewer repetitive questions, and big reductions in time spent hunting for information.3

External investors echo this: Sapphire Ventures calls it “the ultimate Work AI platform” and highlights cross‑system intelligence and agent capabilities as major differentiators.4

Glean vs. traditional enterprise search: what actually improves?

1.2 Evidence it’s genuinely effective

Customer case studies and quantified outcomes

  • Super.com (travel/fintech) reports that Glean helped them supercharge productivity and knowledge management, with published figures of 1,500+ hours saved per month and 20% faster employee onboarding via quicker access to internal knowledge and reduced back‑and‑forth questions.35
  • Confluent reports saving 15,000+ hours per month by standardizing on Glean for internal search and knowledge discovery, specifically crediting the platform’s ability to surface relevant docs and experts across systems.6
  • Glean’s public customer stories catalogue shows similar themes at a mix of tech, services, and industrial customers: reduced time to find information, fewer Slack/Teams pings, and faster new‑hire ramp.7

These are vendor‑curated stories, but they are concrete, named references rather than anonymous claims. A Forrester Total Economic Impact (TEI) study commissioned by Glean models material productivity and support‑ticket deflection benefits from consolidated AI search and agents.8

Independent and ecosystem commentary

  • A detailed third‑party review from Slite describes Glean as “a powerful AI enterprise search platform” and notes that, compared with basic search, relevance, semantic understanding, and people‑graph signals feel significantly stronger in real use.9
  • A Medium review by a practitioner characterizes Glean as “the AI-powered enterprise search that’s actually amazing”, praising answer quality and context awareness across tools like Google Workspace, Slack, Jira, and Notion.10
  • Glean appears as a Customers’ Choice in Gartner Peer Insights for Insight Engines (4.5/5 across ~100 reviews)11 and holds a 4.8+ rating on G2 in the Work AI / enterprise search category, indicating broadly positive user sentiment beyond marketing sites.12

Technical differentiation vs. legacy search

  • Glean emphasizes hybrid retrieval (dense + sparse), rich entity and people graphs, and “first‑order retrievability” (ensuring the most important doc can be found with reasonable queries). An engineer‑authored post and talks describe dedicated work on tuning embeddings and ranking specifically for enterprise RAG use cases.1314
  • Its own and third‑party content highlight features that traditional portal search usually lacks: answer synthesis, conversational refinement, and proactive agents (e.g., surfacing relevant runbooks or docs inside tools like Jira or Salesforce rather than only on a separate search page).How good is Glean’s RAG / retrieval compared to peers?

1.3 Where reality is more nuanced

Search quality is highly data‑ and change‑management‑dependent

  • Even Glean’s own blog stresses that enterprise search is hard and historically "behind" because of fragmented systems, inconsistent permissions, and low content quality.15
  • External commentary (e.g., GoSearch‑authored pieces positioning their own product) argues that “inside Glean’s billion‑dollar hype cycle” a lot of perceived magic is actually careful tuning and ops that not all customers execute well; they suggest that if taxonomy, connectors, or governance are mis‑configured, you can still get noisy or misleading results.16

Vertical and use‑case fit matters

  • Some comparison pieces (e.g., Glean vs. Moveworks, Glean vs. ChatGPT Enterprise, Glean vs. Agentspace) argue that for certain vertical or support‑ticket workflows, a more specialized assistant or ITSM‑integrated tool can deliver better out‑of‑the‑box value than a general Work AI platform.1718
  • Reviews and alternatives lists note that Glean is strongest when you standardize on it as the core knowledge layer; if teams only half‑adopt it (continuing to live in Slack, Confluence, etc.), search benefits are diluted.19

No evidence of Glean being worse than traditional search on quality

  • Critical pieces and alternatives comparisons argue about price, openness, and vendor lock‑in, but there is little credible evidence that Glean delivers inferior search quality to a well‑run SharePoint/Elastic/Lucene stack. The main criticism is “expensive, proprietary, and overkill for small orgs”, not “its search is bad.”Glean vs. open‑source search stacks (Elastic/OpenSearch/etc.)

1.4 Verdict on search & productivity

  • Substantial evidence (named case studies, TEI model, third‑party reviews, and ratings) supports the claim that Glean can materially improve knowledge discovery and productivity vs. traditional enterprise search, especially in mid‑ to large‑scale knowledge organizations.
  • Gains are not automatic: they depend on content quality, connector coverage, permission hygiene, and change management.
  • The main “hype” element is around how plug‑and‑play the impact is; the technology is real, but success still requires serious implementation work.

2. Security, Privacy, and Compliance: Enterprise‑Grade or Over‑sold?

2.1 What Glean markets

Key security and compliance claims from Glean’s own materials:

  • Zero‑trust, modern security foundations; defense‑in‑depth controls with strong isolation and least‑privilege access.20
  • Permission‑respecting search and generative answers – users only see what they are allowed to see based on source‑system permissions, enforced at query and index time.2122
  • Enterprise compliance posture including SOC 2, strong data‑at‑rest and in‑transit encryption, and data residency controls for certain regions.2324
  • Active data and AI governance to monitor usage, protect sensitive content, and apply policy‑driven controls to agent behavior.25

How strong is Glean’s security posture compared to peers?

2.2 Evidence supporting the claims

Formal posture & docs

  • Glean’s security page describes a zero‑trust architecture, SSO/SAML integration, SCIM provisioning, granular permissions, and audit logging.20
  • Developer docs and connector docs show fine‑grained permission modeling: for example, SharePoint connector security documentation details how Glean mirrors document‑ and site‑level ACLs and supports admin controls for sensitive locations.26
  • A Glean blog series on security, permissions‑aware AI, and agent governance describes design patterns for permissions‑aware RAG, including filtering at retrieval time and policy layers to avoid over‑broad data exposure.27[^secure-genai]

Compliance and third‑party signals

  • Glean promotes a SOC 2 posture and is listed in SOC‑2‑oriented partner/ISV ecosystems; a widely shared LinkedIn post from Glean’s account celebrates achieving SOC 2 and emphasizes privacy and security controls.24
  • A separate company, Glean.ai (AP automation, not search) has its own SOC 2 Type II certification announcement,28 which is sometimes conflated with Glean Technologies in casual discussion. They are distinct products, but the confusion itself is a reminder to scrutinize which Glean a security claim refers to.

Customer and partner context

  • Case studies with customers like Confluent and Super.com imply that Glean has passed enterprise security reviews in cloud‑native, data‑sensitive environments.65
  • Glean integrates with Microsoft Agent 365 and is promoted as delivering "enterprise‑ready AI" in Microsoft 365 environments; such integrations normally require baseline security and compliance alignment.2930

Security‑aware ecosystem content

  • Security‑focused partners (e.g., NimbleGravity) publish guidance on “how Glean makes generative AI work secure for business”, describing patterns like restricting training data, honoring source permissions, and isolating tenant data.31

2.3 Evidence of risks, gaps, and criticism

Dedicated security‑risk write‑up

  • SaaS security vendor DoControl published “Glean Security Risks You Need to Know”, outlining potential issues such as:
    • Expanding the blast radius of misconfigured permissions (if a source system already over‑shares, Glean can make that data more discoverable).
    • The risk of over‑permissive API tokens and service accounts.
    • The importance of monitoring AI tools for exfiltration pathways.32
  • The article does not document a known breach at Glean; it frames these as risks to manage when adopting any enterprise AI search platform.

General AI‑data‑leak concerns applied to Glean‑like tools

  • A widely shared LinkedIn post by a security researcher argues that tools like Copilot and Glean can “leak data as a feature” if organizations do not keep permissions and DLP controls tight, because they surface content that was technically accessible but practically obscure.33
  • Broader AI‑security literature (including work on AI agents and SaaS security) highlights:
    • Prompt‑level data leakage.
    • Cross‑system correlation of sensitive data.
    • Shadow data copies and long‑lived indexes.343536 These risks apply to Glean’s category generally, not uniquely to Glean.

Notably absent: public breach reports

  • Searches across breach lists, data‑breach round‑ups, and news articles did not uncover any widely reported, confirmed security breach or compliance failure specific to Glean Technologies as of late 2025.
  • The most concrete "negative" signals are risk advisories and the general class of AI data‑exposure concerns, not documented incidents.

2.4 Practical implications

  • Glean’s architecture, documentation, and enterprise adoption pattern are reasonably consistent with serious security engineering rather than pure hype.
  • However, its permission‑aware AI is only as strong as your underlying IAM and content ACLs. If your SharePoint/Drive/Confluence is a permissions mess, Glean will make that mess more visible.
  • Security teams need to treat Glean like any powerful data access layer: enforce least privilege, short‑lived tokens, connector‑level scoping, and DLP/monitoring.

2.5 Verdict on security & compliance

  • On available evidence, Glean’s security and compliance posture is credible and enterprise‑grade, but not magic. It does what it says technically, yet it cannot compensate for poor customer permission hygiene or governance.
  • There is no public evidence that its security promises are fraudulent; the main concern is operational risk if customers treat “permission‑aware AI” as a substitute for hard IAM work.

3. Deployment, Integration, and Ongoing Operations

3.1 What Glean promises

Glean’s messaging emphasizes:

  • Fast time‑to‑value: connect major SaaS systems and get useful search and agents quickly.
  • A broad catalog of native connectors (Google Workspace, Microsoft 365, Slack, Jira, GitHub, Salesforce, etc.), with a modern connector framework.3738
  • A central admin console with analytics, audit logs, policy controls, and governance features aimed at making operations manageable for IT and security teams.39

How heavy is a typical Glean deployment in a large org?

3.2 Evidence of smooth deployment and quick impact

Customer stories citing fast rollout and value

  • Super.com reports that adopting Glean helped them centralize knowledge for a distributed workforce, reduce ad‑hoc questions, and speed up employee onboarding; the case study presents this as a relatively fast rollout delivering clear benefits.5[^super-bi]
  • Glean’s general customer‑stories index includes narratives where organizations quickly hook Glean into core systems and report measurable time savings within months, not years.7

Connector depth and admin tooling

  • The Glean connectors page lists many first‑party connectors and highlights an advanced connector framework designed to ingest and keep in sync content from dozens of systems. A technical explainer video walks through how this framework avoids some pitfalls of naïve federated search.37[^connector-video]
  • Connector documentation (e.g., for Google Workspace, Microsoft 365, Jira, GitHub, Salesforce) suggests mature handling of permissions, incremental sync, and admin scoping options.38
  • The admin console docs show features like audit logs, policy management, and usage analytics, allowing admins to monitor adoption and fine‑tune scope.4039

Third‑party commentary

  • Comparisons like BA Insight vs. Glean acknowledge that Glean offers a modern SaaS‑native deployment model versus traditional search software that might require heavy infrastructure work.[^bainsight]
  • A Forrester TEI analysis attributes part of the projected ROI to rapid deployment via cloud delivery and pre‑built connectors, compared to custom Elastic/Solr implementations.8

3.3 Evidence of friction, cost, and complexity

Cost and infra‑related concerns

  • GoSearch’s “Glean infrastructure cost breakdown” post analyzes a 20‑user proof‑of‑concept and argues that under the hood, Glean’s architecture can be expensive to run at scale, implying that enterprise customers should expect significant spend relative to DIY or lighter tools.41
  • Other alternatives lists and pricing explainers complain that Glean’s pricing is opaque and premium, noting that smaller organizations may find it overkill relative to lighter AI search tools.424344

Operational and adoption challenges (category‑wide)

  • Glean’s own content on aggregating information across systems and on benefits and challenges of AI adoption acknowledges that stitching together many legacy and SaaS systems is non‑trivial and often blocked by integration challenges, data quality issues, and internal change management.4546
  • Articles about legacy system integration and workflow automation pitfalls (though not Glean‑specific) reinforce that introducing an AI layer over fragmented backends is inherently complex, often requiring multi‑team coordination, process redesign, and ongoing tuning.4748

Direct negative or skeptical commentary

  • A Medium article from GoSearch’s team, “inside Glean’s billion‑dollar hype cycle”, portrays Glean as powerful but heavy, arguing that some customers underestimate the data modeling and integration work needed, leading to disappointing early outcomes.16
  • Various “Glean alternatives” posts (by vendors like Docket, Capacity, TextCortex, and others) emphasize that Glean is best suited to large enterprises willing to invest in rollout and governance, while smaller or less mature orgs may find setup and operations too involved for their resources.494443

Notably, many of these skeptical sources have commercial incentives (they sell competing tools), so they’re better read as highlighting real categories of friction rather than neutral head‑to‑head benchmarks.

3.4 Verdict on deployment & operations

  • For organizations with mature IT and security teams, there is credible evidence that Glean can be deployed and deliver benefits within months, leveraging its connector catalog and SaaS model.
  • Deployment is not trivial: success requires careful connector scoping, permission mapping, content cleanup, and change management. It is closer to an enterprise platform implementation than a weekend side‑project.
  • Critics are right that Glean is not the simplest or cheapest option; for smaller orgs or narrow use cases, it may be more platform than you need.

4. Overall Assessment: Good or Hype?

4.1 What’s real

Across independent reviews, investor and partner write‑ups, TEI modeling, and multiple named customer stories, several things appear solidly grounded:

  • Search & productivity: Glean meaningfully improves information findability and reduces "where is X?" friction in knowledge‑heavy organizations, with concrete time‑savings figures from customers like Super.com and Confluent.56
  • Security posture: Its architecture, docs, and ecosystem integrations are consistent with serious enterprise security, including zero‑trust principles, permission‑respecting retrieval, SOC‑style controls, and data‑governance tooling.2025
  • Platform maturity: Connector depth, admin tooling, and ongoing product releases (e.g., Enterprise Graph, third‑generation assistant, Microsoft Agent 365 integration) suggest an actively developed, mature platform rather than a thin wrapper on generic LLMs.5030

4.2 Where the hype lives

The "hype" is less about outright falsehoods and more about how easy and universal the wins are:

  • Implementation effort is real – you still have to fix permissions, clean content, and drive adoption. Glean acknowledges this in its own blogs, but top‑line marketing can underplay the depth of this work.1545
  • Risk is shifted, not eliminated – permission‑aware AI can amplify existing over‑permissive configurations. Independent security vendors warn about this and position their products as guardrails.3235
  • Fit matters – Glean shines in multi‑app, knowledge‑heavy enterprises; for small teams or very constrained domains, a lighter tool or vertical assistant may be a better trade‑off.1744

4.3 If you’re deciding whether to adopt Glean

Questions and checks that matter more than the marketing:

  1. Size and complexity of your environment

    • Do you have enough scattered SaaS/content systems (Google/M365, Slack/Teams, Jira, GitHub, Salesforce, Confluence, etc.) that a cross‑system Work AI layer is worth the platform investment?

  2. Permission hygiene and governance

    • Are your identity, groups, and content ACLs in decent shape? If not, plan a permission clean‑up project in parallel with any Glean rollout.

  3. Change‑management capacity

    • Do you have owners in IT, security, and business units who can drive rollout, tune connectors, and evangelize use cases? Glean performs best when it becomes a front door for knowledge across teams.

  4. Risk tolerance and vendor posture

    • Treat Glean as a powerful data‑access and agent layer. Ask for security and compliance documentation, including SOC reports, data residency options, and details on tenant isolation and permissions enforcement.

  5. Comparative pilots

    • For serious evaluation, many buyers run side‑by‑side pilots with internal search baselines (e.g., native M365/Google search or Elastic/OpenSearch) and sometimes a competitor like Moveworks, GoSearch, or a homegrown RAG system.How to run a fair pilot: Glean vs. your existing search

4.4 Bottom line

  • For mid‑ to large‑size knowledge‑heavy organizations with the appetite to run a proper implementation, Glean is more "good" than "hype": it is a capable, well‑engineered Work AI platform with strong search, growing agent features, and credible security posture.
  • The main caveats are cost, implementation complexity, and the need for strong internal governance. If you expect a magic "turn it on and everything is solved" product, the hype will burn you; if you treat it as a strategic platform, the available evidence suggests it can deliver on most of what it promises.

5. Helpful Follow‑Up Questions

Footnotes

  1. Glean home page – Work AI positioning, ratings, and high‑level claims. https://www.glean.com/ ↩

  2. Glean AI enterprise search & knowledge discovery guide. https://www.glean.com/resources/guides/glean-ai-enterprise-search-knowledge-discovery ↩

  3. Glean blog, "How Super.com supercharged productivity and knowledge management through Glean". https://www.glean.com/blog/how-super-supercharged-through-glean ↩ ↩2

  4. Sapphire Ventures, "The ultimate Work AI platform – why we’re excited to back Glean". https://sapphireventures.com/blog/the-ultimate-work-ai-platform-why-were-excited-to-back-glean/ ↩

  5. Glean Super.com customer story – 1,500+ hours/month saved and 20% faster onboarding. https://www.glean.com/resources/customer-stories/super ↩ ↩2 ↩3 ↩4

  6. Glean Confluent customer story – 15,000+ hours/month saved. https://www.glean.com/resources/customer-stories/confluent ↩ ↩2 ↩3

  7. Glean customer stories index. https://www.glean.com/resources/customer-stories ↩ ↩2

  8. Forrester TEI of Glean (Work AI Platform). https://tei.forrester.com/go/Glean/workAIplatform/ ↩ ↩2

  9. Slite "Glean Review – Should it be your Enterprise Search tool?" https://slite.com/en/learn/glean-ai-review ↩

  10. Medium, "Glean, the AI-powered enterprise search that’s actually amazing". https://maze-runner.medium.com/glean-the-ai-powered-enterprise-search-thats-actually-amazing-0139650a7ae2 ↩

  11. Glean site – Gartner Peer Insights Customers’ Choice 2024 (Insight Engines). https://www.glean.com/ ↩

  12. Glean homepage / ratings section noting 4.8+ G2 rating. https://www.glean.com/ ↩

  13. Dev.to, "How Glean leverages hybrid search for accurate and efficient enterprise AI". https://dev.to/torinmos/how-glean-leverages-hybrid-search-for-accurate-and-efficient-enterprise-ai-15jj ↩

  14. LinkedIn, "Delivering first-order retrievability in Glean search". https://www.linkedin.com/pulse/delivering-first-order-retrievability-glean-search-curtis-conley ↩

  15. Glean blog, "Enterprise search is hard: why it’s so behind—and what it’ll take to catch up". https://www.glean.com/blog/enterprise-search-is-hard-why-its-so-behind-and-what-itll-take-to-catch-up ↩ ↩2

  16. Medium (GoSearch), "Inside Glean’s billion-dollar hype cycle and the search alternative quietly taking over". https://medium.com/@GoSearch-AI-Enterprise-Search/inside-gleans-billion-dollar-hype-cycle-and-the-search-alternative-quietly-taking-over-1e358f3d2e24 ↩ ↩2

  17. Budibase blog, "Glean vs Moveworks". https://budibase.com/blog/alternatives/glean-vs-moveworks/ ↩ ↩2

  18. Credal.ai blog, "Glean vs Agentspace". https://www.credal.ai/blog/glean-vs-agentspace ↩

  19. Eesel.ai blog, "Glean AI" (review / alternatives). https://www.eesel.ai/blog/glean ↩

  20. Glean Security page. https://www.glean.com/security ↩ ↩2 ↩3

  21. Glean developer docs – permissions model in indexing API. https://developers.glean.com/api-info/indexing/documents/permissions ↩

  22. Glean blog, "Secure generative AI for the enterprise requires the right permissions structure". https://www.glean.com/blog/secure-generative-ai-for-the-enterprise-requires-the-right-permissions-structure ↩

  23. Glean Legal / platform overview. https://www.glean.com/legal ↩

  24. LinkedIn – Glean post on SOC 2/privacy/security. https://www.linkedin.com/posts/glean-ai_soc2-privacy-security-activity-7241844007037779969-IKIZ ↩ ↩2

  25. Glean blog, "Glean active data and AI governance protects enterprise data for the age of agents". https://www.glean.com/blog/data-gov-product-blog ↩ ↩2

  26. Glean docs – SharePoint connector security controls. https://docs.glean.com/connectors/native/sharepoint/security/controls ↩

  27. Glean perspectives, "Enhancing AI security with permissions-aware frameworks". https://www.glean.com/perspectives/security-permissions-aware-ai ↩

  28. Glean.ai blog, "Glean.ai Secures SOC 2 Type II Certification". https://www.glean.ai/post/glean-ai-secures-soc-2-type-ii ↩

  29. Glean press release, "Glean integrates with Microsoft Agent 365". https://www.glean.com/press/glean-integrates-with-microsoft-agent-365-to-deliver-enterprise-ready-ai-where-microsoft-365-users-work ↩

  30. Glean blog, "Glean integrates with Microsoft Agent 365, bringing enterprise context to Microsoft Word, ...". https://www.glean.com/blog/glean-microsoft-integration-2025 ↩ ↩2

  31. NimbleGravity, "How Glean makes generative AI work secure for business". https://nimblegravity.com/blog/how-glean-makes-generative-ai-work-secure-for-business ↩

  32. DoControl blog, "Glean Security Risks You Need to Know: A Guide on Adopting AI Securely". https://www.docontrol.io/blog/glean-security-risks ↩ ↩2

  33. LinkedIn, comment on Copilot and Glean leaking data if misconfigured. https://www.linkedin.com/posts/gadievron_llms-like-copilot-and-glean-leak-data-as-activity-7265820894327963648-amVn ↩

  34. Glean blog, "What is AI security?". https://www.glean.com/blog/what-is-ai-security ↩

  35. Metomic, "The Hidden Data Leakage Crisis: How GenAI Tools Compromise Enterprise Security". https://www.metomic.io/resource-centre/the-hidden-data-leakage-crisis-how-genai-tools-compromise-enterprise-security ↩ ↩2

  36. SentinelOne, "AI Security Risks". https://www.sentinelone.com/cybersecurity-101/data-and-ai/ai-security-risks/ ↩

  37. Glean connectors overview. https://www.glean.com/connectors ↩ ↩2

  38. Glean Help Center – connectors. https://docs.glean.com/connectors/home ↩ ↩2

  39. Glean docs – About the Admin Console. https://docs.glean.com/administration/about ↩ ↩2

  40. Glean docs – Admin audit logs. https://docs.glean.com/administration/management/audit-logs/admin-audit-logs ↩

  41. GoSearch blog, "Glean infrastructure cost breakdown: what a 20-user POC tells us". https://www.gosearch.ai/blog/glean-infrastructure-cost-breakdown/ ↩

  42. GoSearch blog, "Glean pricing explained — and why buyers want more transparency". https://www.gosearch.ai/blog/glean-pricing-explained/ ↩

  43. Capacity blog, "Glean alternatives". https://capacity.com/blog/glean-alternatives/ ↩ ↩2

  44. Docket blog, "Top 11 Glean alternatives & competitors". https://www.docket.io/blog/glean-alternatives ↩ ↩2 ↩3

  45. Glean perspectives, "Challenges in aggregating information across systems". https://www.glean.com/perspectives/aggregating-information-across-systems ↩ ↩2

  46. Glean perspectives, "The benefits and challenges of AI adoption in organizations". https://www.glean.com/perspectives/benefits-and-challenges-ai-adoption ↩

  47. DevSquad, "How to integrate legacy systems: top challenges and strategies". https://devsquad.com/blog/integrate-legacy-systems ↩

  48. Multi‑shoring, "Challenges in implementing workflow automation". https://multishoring.com/blog/challenges-in-implementing-workflow-automation/ ↩

  49. TextCortex, "Best Glean alternatives". https://textcortex.com/post/best-glean-alternatives ↩

  50. SiliconANGLE, "Glean introduces Enterprise Graph, new personalization features for Glean Assistant". https://siliconangle.com/2025/09/25/glean-introduces-enterprise-graph-new-personalization-features-glean-assistant/ ↩

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