How to build a searchable team knowledge base with AI

By the end of this guide you will have a team knowledge base that people can search in plain language, with the important documents connected or written, owners assigned and AI answers that point back to their sources. The AI part is search and drafting on top of your own content: it finds the right page, summarizes it and helps write what is missing.

If you want an AI knowledge base for teams, the first decision is whether your content already lives in many apps (so you need search across them) or whether you need a place to write it down (so you need a wiki or help centre). This guide compares six tools from our Productivity category and covers the steps in order.

Key takeaways

• Decide what the knowledge base must answer, connect or write the sources, check that permissions are respected, then test with real questions before rollout.
• The main decision is search across existing apps, a governed company index, a wiki you write in, or a self-hosted system you control.
• Many enterprise tools do not publish prices. Glean and Guru direct you to sales, while Confluence has a Free plan for up to 10 users.
• Cited answers still need maintenance. Out-of-date pages produce out-of-date answers, so assign owners and review dates.

What you need before you start

• A list of questions. Ten to twenty real questions staff ask often, such as how to book leave or where the latest pricing deck is.
• Your sources. The apps, drives and documents that hold the answers, and who can access each.
• An admin. Someone able to connect apps and manage permissions.
• Time. A pilot can be set up in a day or two for a small team. Large rollouts take longer and often need vendor help.
• Difficulty. Easy for a wiki, moderate for cross-app search, harder for a self-hosted system.
• Data care. Know what is confidential and check each vendor's security statements and your own policies before connecting HR, legal or customer data.

Which kind of AI tool fits this job

Pick by where your content lives and how much control you need.

Search and answers across the apps you already use. Glean connects to the apps a company already uses and lets employees search, ask questions and build agents on that data. Answers respect each user's existing permissions, and it connects to more than 275 work apps and data sources. It is aimed at large organizations, and pricing is by request.

A governed, verified company index. Guru pulls information from more than 100 connected sources into one governed index and delivers answers with citations. AI finds duplicate or conflicting content and drafts documentation, and experts review and approve drafts before they enter the knowledge base. Permissions are inherited from the original systems.

A workspace where you write and organize the content. Notion AI adds agents, enterprise search across connected apps, AI meeting notes and database autofill inside the Notion workspace. Confluence is Atlassian's team wiki, with spaces, labels, whiteboards and databases, and Rovo AI search, chat and agents on Standard and above.

A help centre for customers and agents. KnowledgeBase is a help centre and internal knowledge tool with an AI article editor, from the company behind LiveChat. Its internal knowledge base needs an active LiveChat licence.

A self-hosted option for teams that must keep data in house. Viglet Turing ES is an open-source platform for enterprise search, retrieval-augmented generation (RAG) with cited answers, and agents that runs on infrastructure you control. You host and operate it yourself.

Step 1: Define what the knowledge base must answer

A knowledge base is judged by whether people find answers, so start with the questions.

1. Collect the questions staff ask most, from chat, email and support tickets.
2. Group them by topic, such as onboarding, policies, product and sales.
3. Note who needs each answer, since some content is for everyone and some is restricted.
4. Pick a first group of questions for a pilot.

Check it worked by having a colleague confirm the list matches what they are asked every week.

Step 2: Choose where the content will live

You end this step with a tool picked and a rough plan for content.

1. If the answers already sit in many apps, compare cross-app search such as Glean and Guru.
2. If the content does not exist yet, pick a place to write it, such as Notion or Confluence.
3. If you also serve customers, look at KnowledgeBase for a public help centre.
4. If data cannot leave your servers, consider Viglet Turing ES, and check you have the people to run it.
5. Compare the plans and limits in the table below.

Check it worked by writing down which tool will hold or index each group of content.

Step 3: Connect or import your sources

The goal is for the tool to see the documents that hold the answers.

1. Connect the apps the tool supports. Guru lists 100+ source connectors, Glean lists 275+, and Notion's Enterprise Search covers Slack, Google Drive, GitHub and other connectors but is labeled beta.
2. Import or write key pages in a wiki: policies, how-tos and FAQs.
3. Remove obsolete or draft documents before indexing, to avoid stale answers.
4. Wait for indexing to finish before testing.

Check it worked by searching for a document you know exists and seeing it returned.

Step 4: Set permissions and ownership

Access control decides whether the knowledge base is safe to roll out.

1. Confirm that answers respect the permissions of the source apps. Glean and Guru both state that they respect or inherit existing permissions.
2. Test with two accounts, one with broad access and one with limited access, and compare results.
3. Assign an owner to each area of content, such as HR policies or product documentation.
4. Decide what is public, internal or restricted, and check external sharing settings.

Check it worked by confirming the limited account cannot see a restricted document in search or in an answer.

Step 5: Use AI to fill gaps and tidy content

AI can draft and organize, but a person must approve what becomes official.

1. Look for gaps: questions with no good answer. Guru lists knowledge gap detection, and KnowledgeBase shows missed searches in its Insights section.
2. Draft missing pages with AI. Guru drafts documentation from conversations, meetings and tickets, Notion AI has Research Mode for drafting documents, and Confluence's Rovo can turn rough notes into drafts.
3. Have the content owner review every AI draft before publishing.
4. Resolve duplicates and conflicts, which Guru's AI can find.

Check it worked by seeing the missing questions from step 1 now have an approved answer.

Step 6: Test with real questions

Run the questions from step 1 through the AI assistant and score the results.

1. Ask each question in plain language, the way a new hire would.
2. Check that the answer is correct and cites a source you can open.
3. Mark wrong, vague or uncited answers, and trace each to a missing or outdated page.
4. Fix the source content rather than patching the answer.
5. For anything legal, HR, medical or financial, have an expert confirm the page the answer cites.

Check it worked by most test questions returning a correct, cited answer on the first try.

Step 7: Roll out, measure and maintain

A knowledge base stays useful through habit, not launch day.

1. Tell staff where to ask and show three example questions.
2. Put it where they work. Glean lists embedded experiences in Slack, Teams, Zoom, GitHub and Miro, and Guru works inside Slack, Microsoft Teams and a browser extension.
3. Review analytics and missed searches regularly, then write the missing pages.
4. Set review dates so pages are checked on a schedule. Guru automates content verification using usage signals, content age and policy rules.
5. Watch AI usage allowances, since some plans draw down credits.

Check it worked by seeing questions in chat drop and searches succeed more often.

Tools for this job compared

Tool	Good fit for	Pricing	Stated limits
Glean	Large organizations searching many apps, on web and API	Contact sales	Prices not published; some queries and agent runs draw on FlexCredits
Guru	Verified, governed knowledge with cited answers, on web, Chrome and API	Contact sales	No public price list; AI work consumes credits from a shared pool
Notion AI	Writing and searching in one workspace, on the web	Free trial, paid from $10/mo (checked 24 Oct 2026)	Free and Plus include only a limited trial of the AI; Enterprise Search is Beta
Confluence	A team wiki with whiteboards and Rovo AI, on the web	Freemium, paid from $5.42/mo (checked 24 Oct 2026)	Free is limited to 10 users and 2 GB of storage; Rovo is on Standard and above
KnowledgeBase	Help centres and agent-facing wikis, on the web	Free trial, paid from $49/mo (checked 24 Oct 2026)	Internal knowledge base needs an active LiveChat licence; extra knowledge bases cost more
Viglet Turing ES	Self-hosted search and RAG with citations	Open source	You host and operate it yourself; model provider keys and costs are yours

Prices and plan limits change, so confirm the current terms on each vendor's site before you subscribe.

Common mistakes to avoid

• Indexing everything at once. Old and conflicting files make answers wrong. Fix it by cleaning one area first and indexing it before you add more.
• Skipping permission tests. An AI search can surface restricted content if permissions are misconfigured. Fix it by testing with a limited account before you launch.
• Treating a cited answer as a verified one. A citation shows where an answer came from, not that the source is right. Fix it by assigning owners and review dates to the pages that answers rely on.
• Buying for AI features your plan lacks. Notion's Free and Plus plans include only a limited trial of its AI, and Confluence's Rovo starts on Standard. Fix it by matching the plan to the feature you need.
• Underestimating self-hosting. A self-hosted system gives control but needs staff to run it. Fix it by checking your engineering capacity first.

How we put this together

This is an evidence-based guide built from each tool's listing in our directory, which is compiled from the vendor's own site and pricing page. It is not a review based on using the tools. We don't rank tools, and nobody paid to be included. Some outbound links may be affiliate links; see our disclosure.

Frequently asked questions

Is there a free way to build a team knowledge base with AI?

Partly. Confluence has a Free plan for up to 10 users, but its Rovo AI starts on Standard. Notion's Free plan includes a limited trial of Notion AI, and Viglet Turing ES is open source but self-hosted. Glean and Guru price through sales.

Can AI answer questions from our internal documents?

Yes. Guru and Viglet Turing ES describe answers with citations, and Glean answers questions from company apps with each user's permissions respected. Check that the cited page is right, and keep pages current so answers stay accurate.

Can I keep company data private?

Check each vendor's statements. Glean and Guru say answers respect existing permissions, and Viglet Turing ES runs on infrastructure you control. Review security certifications, data terms and your own policies before connecting sensitive systems.

How long does it take to set up?

It depends on how much content you have and how many apps you connect. A small pilot is mostly time spent choosing content and checking permissions, while enterprise search across many apps usually involves an admin and the vendor.

Which tool works for a help centre rather than internal use?

KnowledgeBase lists a public help centre for customers and an internal knowledge base for agents, with custom branding and a custom domain. Its internal knowledge base requires an active LiveChat licence.

Compare more options in our Productivity category. To write the process docs that fill a knowledge base, see How to write SOPs and process docs with AI.