Glean vs Guru: Broad Permissions-Aware Search or Verified, Curated Answers?
Glean is a broad, enterprise-oriented AI search and assistant platform that connects to dozens of workplace apps with permissions-aware results; Guru is a narrower, curation-first platform built around expert-verified knowledge cards for teams that prioritize trust over raw coverage.
There is no categorical winner here, the two tools are built around different bets. Glean is the broader, enterprise-oriented AI search platform, built to index dozens of connected workplace apps and answer questions with permissions-aware results that respect each source system's own access controls, which fits a larger organization that wants wide coverage with minimal manual curation. Guru is narrower by design: it centers on knowledge cards that a subject-matter expert writes, verifies, and periodically re-confirms, surfaced through a browser extension and native Slack and Microsoft Teams integrations, which fits a team that cares more about trusting the answer than about searching everything at once. Both are sold mostly or entirely through custom-ish, less transparent pricing, so budgeting for either means getting a direct number rather than reading a public rate card.
Glean and Guru both get filed under the same AI internal knowledge assistant category because both let employees ask a question and get an answer instead of a pile of search results, but they start from different assumptions about where that answer should come from. Glean assumes the right answer is already sitting somewhere in one of the dozens of systems a company already runs, Slack, Google Drive, Confluence, Jira, Salesforce, GitHub, and more, and its job is to index all of it, respect the permissions already set in each system, and let an AI assistant or agent pull from whichever source actually has the answer. That is a connector-breadth and permissions-engineering problem, and it is built and priced for organizations complex enough to need that scale.
Guru assumes the opposite: that raw indexed documents are often outdated, scattered, or simply wrong, and that the fix is a human-in-the-loop layer where a subject-matter expert writes a short knowledge card, verifies it is accurate, and is prompted to periodically re-confirm that it still is. Guru's Knowledge Agents then answer questions in Slack and Microsoft Teams, or through a browser extension side panel, using only that verified content. It is a curation-and-trust problem rather than a coverage problem, and it is priced and packaged for a narrower, more governance-conscious use case, support, success, and enablement teams in particular, rather than an attempt to index everything a company owns.
Feature-by-Feature Comparison
| Feature | Glean | Guru |
|---|---|---|
| Core model | Broad AI search and assistant layer indexing dozens of connected apps | Curated knowledge cards with an expert-verification workflow |
| Connector breadth | Vendor-cited at 275+ native connectors (Slack, Google Drive, Confluence, Jira, Salesforce, GitHub, Microsoft 365, and more) | Narrower integration set, centered on Slack, Microsoft Teams, and a browser extension rather than dozens of indexed source systems |
| Permissions model | Permissions-aware search and AI answers that inherit and enforce each connected system's own access controls, synced close to real time | Access controlled at the Guru workspace and role level (SSO, SCIM, RBAC on Enterprise) rather than inherited per-source-system permissions across dozens of apps |
| Knowledge trust model | Answers are generated from whatever is indexed; accuracy depends on how well-maintained the source documents already are | Knowledge cards are explicitly authored and verified by subject-matter experts, with a Verification Score tracking what percentage is current |
| Where answers surface | Glean Assistant chat interface, plus Glean Agents for multi-step automated tasks | Knowledge Agents inside Slack and Microsoft Teams channels, @mention answers, and a persistent browser extension side panel |
| AI answer quality driver | Breadth of connected sources plus real-time permission filtering | Narrower but higher-confidence answers, bounded by what has actually been verified |
| Pricing model | Entirely custom-quoted, no published rate card; third-party estimates put per-seat cost around $40-50/user/month with a seat minimum commonly around 100 | Self-serve plan reported around $25-30/seat/month with a smaller (commonly ~10-seat) minimum, plus a custom-quoted Enterprise tier |
| Free offering | No permanent free plan; sales-led evaluation window, commonly reported around 30 days | A 30-day free trial is consistently reported; sources disagree on whether a permanent free tier currently exists |
| Standout differentiator | Breadth: one AI layer across the widest practical set of connected enterprise systems | Trust: a visible, ongoing verification workflow that tells readers (and the AI) what has actually been checked |
| Best fit | Larger organizations that need broad, permissions-aware AI search across many connected systems | Teams, especially support, success, and enablement, that want governed, expert-verified answers over raw search reach |
Pricing Compared
| Tier | Glean | Guru |
|---|---|---|
| Entry / trial | Sales-led evaluation, commonly reported around 30 days, no self-serve signup | 30-day free trial of paid plans is consistently reported; a permanent free tier is disputed across sources |
| Self-serve / mid tier | Not available; Glean has no self-serve tier | Roughly $25-30/seat/month billed annually, commonly with a 10-seat minimum (a practical floor near $250-300/month) |
| Enterprise | Custom quote; third-party estimates put annual contract values roughly in the $30,000 to $200,000+ range, with per-seat figures around $40-50/user/month (some reports closer to $75) | Custom quote, with SSO, SCIM, RBAC, and compliance certifications (SOC 2 Type II, reported HIPAA/GxP) layered in |
Neither vendor publishes a confirmed, official rate card for every tier. All figures above are third-party buyer-reported estimates current as of late 2026, not vendor-quoted prices, and actual cost for either tool depends on seat count, scope, and negotiated terms.
Neither Glean nor Guru publishes a complete, official rate card. The figures in this comparison are third-party buyer-reported estimates current as of late 2026, not confirmed vendor pricing, and actual cost for either tool depends heavily on seat count, scope, and negotiated terms. Verify current numbers directly with each vendor before budgeting.
Pros & Cons
Glean
Pros
- ✔ One of the broadest native connector libraries in the category, reducing how many systems sit outside the searchable, assistant-accessible index
- ✔ Permissions-aware search is a genuine enterprise-grade differentiator, lowering the risk of AI surfacing something an employee could not already access
- ✔ Glean Agents extends the platform from answering questions into automating multi-step work on top of the same indexed knowledge
Cons
- ✕ No published pricing anywhere, and a seat minimum commonly reported around 100 makes it impractical for smaller teams regardless of per-seat cost
- ✕ No permanent free plan, only a time-limited sales-led evaluation
- ✕ Answer quality still depends entirely on how well-maintained the underlying connected documents are; Glean has no formal expert-verification layer of its own
Guru
Pros
- ✔ The verification workflow and Verification Score give teams a concrete, visible signal of which answers have actually been checked by a human expert
- ✔ Native Slack and Microsoft Teams integration plus a browser extension put verified answers directly inside the tools people already use
- ✔ Lower practical entry cost and a smaller reported seat minimum than Glean, with a clear 30-day trial
Cons
- ✕ Narrower connector and raw-search breadth than a platform built to index dozens of enterprise systems at once
- ✕ The entire trust model depends on experts actually doing the verification work; an unmaintained card set undercuts the core value proposition
- ✕ Pricing details, including whether a permanent free tier exists, are inconsistent across third-party sources and need direct confirmation
Which One Should You Actually Pick
You need one AI layer across dozens of connected enterprise systems
Glean is built for exactly this. Its connector breadth and permissions-aware search are engineered for organizations running many overlapping systems that all need to be searchable in one place.
Your priority is trusting the answer, not just finding one
Guru's knowledge cards and verification workflow give subject-matter experts a direct way to confirm accuracy and keep it current, which matters most for support, success, and enablement teams where a wrong answer has real consequences.
You have a small or mid-size team with limited budget
Guru's self-serve plan and smaller seat minimum make it the more accessible starting point. Glean has no self-serve tier and typically requires a seat count and budget that only make sense for larger organizations.
You have the connected systems but not the people to maintain a curated knowledge base
Glean's model doesn't require a dedicated expert to write and verify cards; it indexes what already exists. Guru's trust model only pays off if someone is actually willing to own verification.
You are deciding based on permissions and security requirements
If the main risk you're managing is an AI surfacing sensitive content from a specific connected system (HR files, deal terms, restricted repos), Glean's per-source permissions inheritance is the more directly engineered answer. If the main risk is misinformation or outdated process docs, Guru's verification layer addresses that more directly.
Why "Which One Is Better" Is the Wrong Question
Glean and Guru both land in AI internal knowledge assistant comparisons because both let an employee ask a question in plain language and get an answer instead of a list of search results to sift through. But they are solving different problems underneath that similar surface. Glean's bet is coverage: index as much of the company's existing app stack as possible, Slack, Google Drive, Confluence, Jira, Salesforce, GitHub, and dozens more, and build a permissions engine robust enough that surfacing all of it to an AI assistant doesn't create a security problem. Guru's bet is trust: narrow the scope to knowledge cards a real subject-matter expert has written and verified, and build a visible workflow that keeps those cards current, rather than trying to make sense of everything a company has ever written down.
The more useful question is which problem your organization actually has. A company running dozens of overlapping systems, where the real pain is that nobody can find anything and IT needs assurance that an AI layer won't leak access it shouldn't, is closer to what Glean is built for. A team, often support, customer success, or sales enablement, where the real pain is that existing documentation is outdated or contradictory and a wrong answer has immediate consequences, is closer to what Guru is built for. Company size matters too: Glean's lack of a self-serve tier and commonly reported 100-seat minimum put it out of reach for most small teams regardless of fit, while Guru's smaller reported seat minimum and self-serve plan make it accessible well before an organization is large enough to justify Glean.
What to Verify Before Choosing
Because neither vendor publishes a confirmed, official rate card for every tier, treat any dollar figure here, including the ones in this comparison, as a third-party estimate rather than a number you can budget against directly. For Glean, get a quote scoped to your actual connector list and seat count, and ask specifically how model usage is billed (pooled credits versus provider API rates), since that can move total cost more than the base per-seat license does. For Guru, confirm the current status of any free tier directly, since third-party sources disagree on whether one is currently permanent, and ask how the reported 10-seat minimum applies if your team is smaller than that.
Also worth raising directly with either vendor: how answer quality actually gets validated day to day. Glean's permissions-aware search solves an access problem, not an accuracy problem, so ask what happens when an indexed document is outdated. Guru's verification workflow solves an accuracy problem for whatever has been written as a card, so ask how gaps, questions with no existing verified card, get surfaced and routed to an expert rather than silently going unanswered.
Common questions
Neither is categorically better, they solve different problems. Glean is built for broad, permissions-aware AI search across dozens of connected enterprise systems, which suits larger, more complex organizations. Guru is built around expert-verified knowledge cards for teams that prioritize trust and governance in a narrower set of answers, which suits smaller or more support-and-enablement-focused teams.
Guru is generally the more accessible option on cost, with a self-serve plan reported around $25-30 per seat per month and a smaller reported seat minimum (commonly around 10 seats). Glean has no self-serve tier at all, sells only through custom quotes, and is commonly reported to carry a seat minimum around 100, with per-seat estimates around $40-50 per month or higher. Neither vendor publishes an official rate card, so these are third-party estimates, not confirmed prices.
Both offer a free evaluation window rather than a confirmed permanent free tier for most buyers. Glean commonly offers a sales-led evaluation reported around 30 days. Guru consistently offers a 30-day free trial of its paid plans, though sources disagree on whether a genuinely permanent free tier is currently available, so confirm directly with Guru.
Glean inherits and enforces the access permissions already set in each connected source system (Slack, Google Drive, Confluence, and so on) in close to real time, so an AI answer should never surface something an employee couldn't already open directly in that system. Guru controls access at the workspace and role level within its own platform (SSO, SCIM, role-based access on Enterprise), which is a simpler model since its content is curated cards rather than a live index of dozens of external systems.
Some organizations do, typically Glean for broad search and assistant coverage across systems, and Guru for a specific team (support or sales enablement, for example) that wants a governed, verified knowledge layer for its own high-stakes answers. It adds licensing and maintenance overhead on both sides, so it generally only makes sense when the two are serving genuinely different needs rather than overlapping ones.
Guru requires more ongoing human effort in a specific way: its entire value depends on subject-matter experts actually writing and periodically re-verifying knowledge cards. Glean requires less manual curation since it indexes existing systems automatically, but answer quality then depends entirely on how well-maintained those underlying source documents already are, and the initial connector setup and permissions configuration is a heavier IT lift.
Not sure whether you need broad permissions-aware search or verified, curated answers?
We'll help you figure out whether a broad platform like Glean or a curation-first platform like Guru actually fits your team's systems, size, and how much expert bandwidth you have to maintain it.
Ready to get started?
We usually reply within 24 hours.