Kelu vs Guru
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Guru is a knowledge platform where teams write and verify knowledge cards, with AI agents that also search your connected apps. Kelu ingests the sources you already have — docs, help desk, Drive, GitHub, and more — and answers questions for both your team and your customers via widget, API, bots and MCP. This comparison is checked against Guru's own site and docs.
Choose Guru if your team wants to write and verify its knowledge in one place, with expert review cycles and answers for employees in Slack, Teams and the browser. Choose Kelu if your knowledge already lives in docs, repos and help desks, and you want it to answer your customers too, through a public widget, helpdesk AI and an MCP server, with public prices.
Feature comparison
The Guru column comes from Guru's own website and help center.
Where Kelu focuses differently
No re-authoring — your existing sources are the knowledge base
Guru's model centers on knowledge cards your team writes and verifies inside Guru. Kelu indexes what you already maintain — docs sites, GitHub repos, Notion, Confluence, resolved help desk tickets, Drive files — and keeps the index current with scheduled syncs. The docs stay where they live.
Answers for customers, not only employees
Kelu ships a public 'Ask AI' widget, a REST API, Slack and Teams bots, a support-form deflector and Support Ticket AI in your helpdesk — so the same knowledge base answers your customers on your docs site and your team in Slack, each with the right permissions.
Developer-grade APIs and an MCP server per knowledge base
An open REST API with streaming, public client keys for the browser, and MCP servers you create per knowledge base mean your knowledge is queryable from AI coding tools, custom apps and external agents — not just inside one product's UI.
Find and close the gaps
Gap analytics cluster unanswered questions, and Knowledge Maintenance drafts answers to close gaps — your team reviews and adds them instead of writing from scratch.
Got questions?
Frequently asked questions
How is Kelu different from Guru?
Guru is a knowledge platform: teams author knowledge cards in Guru, experts verify them, and Knowledge Agents answer employees from those cards and connected apps. Kelu ingests the sources you already have — docs sites, repos, wikis, help desks, Drive — and answers questions with citations for both your team (internal Ask assistant, Slack and Teams bots) and your customers (widget, API, helpdesk AI, MCP).
Can Kelu replace Guru for internal knowledge?
If your knowledge already lives in docs, Notion, Confluence, Google Drive, OneDrive, or repos, yes — Kelu indexes those directly into internal knowledge bases with per-knowledge-base permissions, and SSO on Enterprise. If your team prefers authoring and verifying knowledge inside a dedicated wiki product, Guru's card model may fit better.
Does Kelu have something like Guru's verification workflows?
Kelu approaches freshness differently: scheduled syncs keep the index matching the live sources automatically, gap analytics surface questions your content doesn't answer, and Knowledge Maintenance drafts answers for those questions that your team reviews and adds or dismisses. There is no per-document expert sign-off like Guru's verifiers.
Does Kelu support the same integrations?
Kelu ships a web widget, a support form deflector, Slack and Microsoft Teams bots, an open REST API with WebSocket streaming, an MCP server per knowledge base, and Support Ticket AI in Zendesk, Intercom, Freshdesk, Front and Linear (tickets) and Freshchat (live chat). React and JavaScript SDKs are on npm.
Do answers include citations?
Yes. Each answer built from your content links to the exact source passages it used.
Is my data used to train AI models?
No. Your connected content and your users' conversations are never used to train models. Content is indexed only to answer questions for your knowledge base. PII masking and zero data retention are available on every plan.
Is this comparison up to date?
The Guru column was checked against Guru's own website and help center on October 29, 2026. The pages we used are listed under the table. If you spot something outdated, contact us and we'll correct it.
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