Guru
Guru positions itself as the governed knowledge layer for enterprise AI. It is a curated company knowledge base whose Knowledge Agents give cited, permission-aware answers and actively maintain the content behind them, auto-verifying and unverifying material as sources change.
The maintenance is the differentiator. Automated knowledge quality detects conflicting content, merges duplicates, flags stale material and identifies gaps, documentation drafts itself from Slack threads, and MCP support lets agents retrieve and act in tools such as Asana, Slack and Salesforce. More than 100 integrations, including real-time Slack search, Teams and a browser extension, put answers where people already work.
It is a sales-led enterprise purchase, packaged to the organisation, with SOC 2 Type II, HIPAA, SSO and audit trails behind it.
- Cost
- Enterprise
- Ease
- Intermediate
- Model
- Hosted service
- Checked
- July 2026
Prices, plans and model versions change fast: this is a mid-2026 snapshot; check the tool's official site for the latest.
Best for
- Cited, permission-aware answers from a verified knowledge base
- Knowledge Agents that maintain content as well as retrieve it
- Automated conflict detection, duplicate merging and stale-content flagging
- Answers inside Slack, Teams and the browser where questions arise
- Regulated organisations needing SOC 2 Type II, HIPAA and audit trails
Less suited to
Guru is bought through a sales conversation and packaged to the organisation, which sets the floor: the scoping assumes real knowledge complexity, governance needs and rollout effort. Small teams wanting a lightweight wiki they can adopt this afternoon are not the buyer here, and workspace tools cover that need with far less ceremony. It is also a knowledge layer rather than a helpdesk, intranet or HRIS; systems of record and ticketing stay where they are.
The verification model has limits worth respecting too. AI-generated answers about policy, legal or compliance content are retrieval aids, not authoritative guidance, and verification workflows reduce but do not eliminate the need for owner review of regulated content.
Costs & data, in short
Guru is an enterprise, sales-led purchase. The official pricing page offers a single package customised to the organisation's scale, knowledge complexity and AI maturity, combining the platform with solution-engineering expertise and enterprise infrastructure. There are no public tiers and Guru no longer offers a free tier publicly; discounted pricing exists for eligible non-profits. Budget for a scoped organisational rollout with a sales conversation at the front, not a tool a single team adopts on its own.
Guru's governance posture is the pitch. SOC 2 Type II, HIPAA compliance, SSO and audit trails, with permission-aware answers that respect role-based scoping, which is what makes deployment in regulated environments plausible. The discipline to keep is editorial rather than technical. AI-generated answers about policy, legal or compliance content are retrieval aids, not authoritative guidance, and the verification workflows that keep content owned and current reduce but do not eliminate owner review of regulated material. It is a closed, hosted platform, so treat connector scope, answer-audit trails and current security documentation as part of the rollout review.
In practice
How Guru is used, area by area.
Operations
Guru gives operations a source of process truth that maintains itself. Every entry names its owner and shows whether it is still verified, Knowledge Agents answer questions with citations and respect for who may see what, and the automated quality layer does the housekeeping operations never gets to: conflicting process docs detected, duplicates merged, stale SOPs flagged, gaps identified. Tribal knowledge stops evaporating because documentation drafts itself from the Slack threads where the real answers were given, and MCP support lets agents retrieve and act in tools such as Asana and Salesforce rather than stopping at the answer. Those answers surface in Slack, Teams and the browser extension, where the questions actually arrive. Operations teams tired of being the company's process helpdesk gain the most.
Example tasks
- Consolidate scattered SOPs into one verified source of truth
- Answer process questions in Slack with cited, permission-aware responses
- Flag stale procedures and surface conflicting process docs for owners
- Draft documentation from the Slack threads where answers already live
- Connect agents to Asana and Salesforce so answers end in actions
Limits
A small operations team wanting a shared wiki does not need a governed knowledge layer, and the sales-led enterprise packaging assumes organisational scale. Guru also stores and verifies knowledge rather than executing it, so workflow automation stays with the platforms built for it.
Where operational content shades into policy or compliance, treat AI-generated answers as retrieval aids rather than authoritative guidance; verification reduces the owner review regulated procedures need but does not remove it.
Compares
| vs | Pick Guru when | Pick the other when |
|---|---|---|
| GleanFull comparison → | Guru keeps the operational canon verified so process answers come from SOPs their owners still stand behind | the estate is too sprawling to curate and the real need is search across every application |
| Notion AI | Guru treats knowledge quality as the product, with conflict detection, staleness flags and verification states an agent can cite | the team already lives in one workspace and wants answers over it without an enterprise procurement |
Customer support
Guru exists for the moment a support agent answers a customer from a stale document. Verification is the product: policies and product answers carry an owner and a verification state, auto-verify and unverify keep that state honest as sources change, and conflict detection catches the two competing refund policies before an agent quotes the wrong one. Knowledge Agents give cited answers scoped by role, so tier-one and outsourced teams see what they should and nothing more, while the browser extension and real-time Slack search put those answers inside the console and the escalation channel rather than a tab away. Guru turns the gaps it identifies into a documentation queue. Support organisations where answer quality is a brand risk and wrong answers compound gain the most.
Example tasks
- Keep refund and policy answers verified before agents quote them
- Scope answers by role so outsourced teams see only their content
- Surface cited answers in the console through the browser extension
- Turn identified knowledge gaps into a documentation queue
- Merge duplicate macros and retire stale product answers
Limits
Guru is the knowledge layer, not the helpdesk: ticketing, routing and customer-facing deflection stay platform work, and a small team on a shared inbox does not need governed verification. The sales-led enterprise packaging sets the floor.
Where support answers touch policy, legal or compliance ground, AI-generated answers remain retrieval aids rather than authoritative guidance; keep owner review of regulated content in place, because verification narrows that duty without ending it.
Compares
| vs | Pick Guru when | Pick the other when |
|---|---|---|
| ScribeFull comparison → | Guru is the verified knowledge base a support floor runs on, with cited answers, ownership and staleness flags across policy and product truth | the gap is step-by-step how-to guides captured automatically while someone performs the process, since enablement budgets usually buy one, not both |
HR & recruiting
HR fields the company's most repeated question set, and Guru turns it into a governed answer layer. Policy, benefits and onboarding knowledge carries owners and verification states, and Knowledge Agents answer employees in Slack and Teams with citations and permission-aware scoping, so manager-only guidance stays with managers while the parental-leave policy reaches everyone. The maintenance layer earns its keep at policy-change time: stale-content flags and automatic unverification catch last year's handbook before it answers this year's question, and gap identification points HR at the policy coverage still missing. New joiners onboard against the same verified base instead of a buddy's memory. HR teams answering the same twenty questions on repeat, where a wrong policy answer has consequences, gain the most.
Example tasks
- Answer benefits and leave questions in Slack with cited policy
- Scope manager guidance away from the general employee audience
- Flag stale handbook content automatically when policies change
- Surface gaps in policy coverage for owners to fill
- Onboard new joiners against a verified knowledge base
Limits
The sales-led packaging is scoped to whole organisations, so an HR team of a handful of people answering questions from one handbook is buying more governance than it needs. Guru is also not an HRIS or an ATS: records, workflows and cases stay in the systems built for them.
Employment policy is regulated ground. AI-generated answers about policy, legal or compliance content are retrieval aids, not authoritative guidance, and verification workflows reduce but do not eliminate owner review before an answer becomes advice.
Compares
| vs | Pick Guru when | Pick the other when |
|---|---|---|
| Sana | Guru is the verified answer layer for the policies and institutional knowledge HR already owns, maintained where employees ask | the need extends into learning itself, with courses, assessments and AI tutoring built over company knowledge |
Search & knowledge retrieval
Guru stakes out the curated end of enterprise knowledge retrieval: rather than indexing everything and ranking what it finds, it maintains a governed layer of verified knowledge and answers from that. Knowledge Agents return cited, permission-aware answers with role-based scoping, and they work the content as well as reading it, auto-verifying and unverifying across sources while conflict detection, duplicate merging, stale-content flags and gap identification keep the corpus answerable. MCP support extends retrieval into action, letting agents fetch and act in tools such as Asana, Slack and Salesforce, and more than 100 integrations put answers where the questions arise. SOC 2 Type II, HIPAA, SSO and audit trails frame it for regulated estates. Organisations that need answers they can defend, not merely answers they can find, gain the most.
Example tasks
- Get cited answers scoped to what each person may see
- Auto-verify and unverify knowledge as connected sources change
- Detect conflicts and merge duplicates across the knowledge base
- Retrieve and act in connected tools through MCP agents
- Audit answer provenance with owners, citations and trails
Limits
If the need is searching an uncurated sprawl exactly as it stands, index-everything work AI fits better; Guru assumes someone will own and verify the knowledge it answers from, and that curation effort is real. The enterprise packaging also rules out teams wanting lightweight workspace Q&A.
Even inside the governed layer, AI-generated answers about policy, legal or compliance content are retrieval aids, not authoritative guidance; verification workflows narrow owner review of regulated content without eliminating it.
Compares
| vs | Pick Guru when | Pick the other when |
|---|---|---|
| GleanFull comparison → | Guru answers from a curated and verified knowledge layer, every answer tracing to content an owner has verified and stands behind | the priority is index-everything work AI across the whole application estate, searching knowledge as it lies rather than as it is curated |
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What is Guru best at?
Guru is strongest for cited, permission-aware answers from a verified knowledge base; knowledge Agents that maintain content as well as retrieve it; automated conflict detection, duplicate merging and stale-content flagging; answers inside Slack, Teams and the browser where questions arise; regulated organisations needing SOC 2 Type II, HIPAA and audit trails.
What is Guru not good for?
Guru is bought through a sales conversation and packaged to the organisation, which sets the floor: the scoping assumes real knowledge complexity, governance needs and rollout effort. Small teams wanting a lightweight wiki they can adopt this afternoon are not the buyer here, and workspace tools cover that need with far less ceremony. It is also a knowledge layer rather than a helpdesk, intranet or HRIS; systems of record and ticketing stay where they are. The verification model has limits worth respecting too. AI-generated answers about policy, legal or compliance content are retrieval aids, not authoritative guidance, and verification workflows reduce but do not eliminate the need for owner review of regulated content.
Is Guru free?
No: Guru is enterprise software, priced per organisation.
Where does Guru fit best?
Guru fits best in Operations and Customer support; see its practice notes for how.
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Last checked: July 2026