7 Best Glean Alternatives for Company Knowledge in 2026

Ask a company search tool what counts as an "active customer" and it returns three documents that disagree. So someone asks a colleague, who explains it in a thread. Next month, a different person asks the same question and gets the same three documents.

Glean is one of the best-known tools for the first half of that problem, because it helps people find what already exists. Some teams outgrow search alone, though, or want a different fit on deployment, ecosystem or cost. This guide compares seven Glean alternatives, shows how to choose between them, and explains where PromptQL's Company Brain fits for teams that need shared knowledge as well as search.

• Glean is a strong benchmark: It connects to many work apps and returns cited, permission-aware answers.
• Alternatives solve different problems: The seven tools below cover ecosystem assistants, knowledge verification, open-source deployment, custom agents and a Company Brain.
• Search and shared knowledge differ: Enterprise search finds what is written down, while a Company Brain captures what your team learns while working.
• PromptQL works alongside search: It turns corrections and decisions into a shared wiki connected to business data, and it does not need to replace Glean.

Glean is an enterprise AI search and assistant platform that connects to your work apps and answers questions with citations. Its materials describe more than 100 connected applications. Its main strengths are:

• Search across connected apps: One query reaches content from many tools instead of one at a time.
• Permission-aware answers: Access controls are checked before an answer reaches the user.
• Cited answers: Citations open the original item in its own app, so people can check the source.
• Search by meaning and keyword: Queries combine both approaches to find relevant results.

Glean also offers personal memory that stores a user's role, preferences and projects. According to Glean's documentation, those memories are kept per user and are not shared between users. That helps personalization but does not build shared team knowledge.

Teams look for Glean alternatives when search alone does not match how they work, or when another tool fits their budget, stack or security needs better. Common reasons include:

• Pricing and contract flexibility: Enterprise platforms often suit larger organizations, and smaller teams may want lighter options.
• Existing ecosystems: Companies built on Microsoft 365, Atlassian or Notion may prefer an assistant that lives in those tools.
• Deployment control: Some teams want to self-host or choose their own language models.
• Knowledge management beyond search: Teams that need verified, maintained answers may want a tool built around content quality.
• AI that works with business data: Finding a document differs from analyzing the numbers behind it, so some teams want shared context connected to their data.

The right tool depends on the problem you are solving.

1. PromptQL

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PromptQL is a multiplayer AI workspace from Hasura where a team works with one shared agent in the same threads. Its Company Brain collects business definitions, decisions and exceptions in a shared wiki, and it connects to sources such as Slack, Google Docs, Snowflake and Salesforce, so a conversation can move straight to analysis.

With search, an answer is only as good as the documents someone wrote. With PromptQL, a colleague can correct an answer or explain an exception in a thread, and that explanation can be added to the wiki. Where per-user memory helps one person, the wiki helps the whole team.

Here is what sets it apart:

• Corrections that become shared knowledge: A fix made once in a thread can be added to the wiki so everyone benefits.
• A wiki with sources and history: Entries link to source data and keep revision history and audit trails, so you can see where a fact came from and who changed it.
• Answers scoped to the person asking: Scopes separate personal, confidential, internal and external data, and queries run under the asker's own permissions.
• Best suited for: Teams that want shared context and business data in one workspace, alongside or instead of search.

2. Microsoft 365 Copilot

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Microsoft 365 Copilot is grounded in your organization's data through Microsoft Graph, which draws on documents, emails, chats and meetings. For companies that already work in Microsoft tools, that makes it a natural choice.

Here is what sets it apart:

• Built into familiar apps: Help appears where people already write, meet and message.
• Outside content through connectors: Copilot connectors bring content from external services into Microsoft Graph so it becomes searchable.
• Existing access controls: Microsoft recommends relying on Microsoft 365 permission models, such as those in SharePoint, so data appears only for people allowed to see it.

Where it fits best: Companies whose work already lives in Microsoft 365.

3. Atlassian Rovo

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Rovo is Atlassian's AI offering, made up of search, chat and agents. It works across Atlassian apps and connected SaaS tools, which suits teams whose projects and documentation live in Jira and Confluence.

Here is what sets it apart:

• Search with a knowledge graph: Rovo Search uses Atlassian's Teamwork Graph to connect information across apps.
• Chat that takes action: Rovo Chat can create Jira tickets or send Slack messages, and Deep Research compiles cited reports.
• Agents you can build: Rovo Studio lets teams build agents and automations without code.

Pick this if: Your team plans and documents work in Atlassian tools. Atlassian says Rovo is included in select plans, so check yours.

4. Guru

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Guru is a knowledge layer built around trust. It connects to existing tools through more than 100 connectors, organizes the content, and routes outdated or conflicting items to experts for review.

Here is what sets it apart:

• Verification workflows: Automated checks flag stale or contradictory content and send it to experts, and verified items are marked as such.
• Cited answers: Its Knowledge Agent returns answers with citations and shows the reasoning behind them.
• Works where teams work: It supports Slack, Microsoft Teams, a browser extension and MCP for other AI tools.

Ideal for: Support, sales and operations teams that need answers they can trust.

5. Onyx

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Onyx is an open-source AI chat and enterprise search platform. Because teams can run it on their own infrastructure, it appeals to companies with strict data control needs.

Here is what sets it apart:

• Self-hosting: Chats, vectors and source documents can stay on infrastructure you control.
• Bring your own model: It works with providers such as OpenAI, Anthropic and Azure, or with self-hosted models.
• Broad connectors: More than 40 connectors pull data from tools such as Google Drive, Slack, Confluence and Jira.

Who it suits: Technical teams that want control over hosting and models and can manage the setup.

6. Dust

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Dust lets teams build AI agents that work with company data and tools. Agents can be created without code, with control over instructions, data sources and tools.

Here is what sets it apart:

• No-code agent building: Non-technical builders can create and customize agents.
• Native data connections: It connects to tools such as Slack, Google Drive, Notion, Confluence and GitHub.
• Model flexibility: It is model-agnostic, with SSO, access control policies and role-based management for admins.

Good match for: Teams that want custom assistants for specific workflows.

7. Notion AI

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Notion AI includes Enterprise Search, which answers questions from your Notion workspace and connected apps such as Slack, Microsoft Teams, Google Drive and Jira. It cites its sources and is available on the Business and Enterprise plans.

Here is what sets it apart:

• Search inside your workspace: Pages and databases are searched alongside connected apps.
• Cited answers: Responses point back to the original sources.
• Familiar interface: Teams that already write in Notion do not need to learn a new tool.

Strongest fit: Teams whose documentation and planning already live in Notion.

Choose the tool that closes your biggest gap, then test it on real questions. Compare options on these criteria:

1. Search: Can it find the right information across your apps and cite where it came from?
2. Knowledge management: Can it keep content accurate, flag stale answers and show who changed what?
3. Business context: Can it learn definitions, exceptions and decisions as well as retrieve documents?
4. Data and integrations: Does it connect to the apps and databases your team uses every day?
5. Security and permissions: Does each person only see what they are allowed to see?
6. Execution: Can it turn knowledge into reports, investigations and workflows?

Tools built for engineering knowledge, such as code-focused assistants, form a separate category and should be judged against their own needs.

Some teams need a Company Brain because search finds what is already written down, while a Company Brain captures what the team learns as it works. The table shows how the three approaches differ:

Think of search as a library and a Company Brain as the colleague who remembers that revenue excludes refunds because someone explained it once. Maintenance is the usual sticking point. Slite's July 2026 survey of 149 teams found that only 17% had a company brain that worked, and another 27% tried and gave up, almost always over maintenance.

PromptQL's Company Brain turns the conversations your team already has into a shared wiki that every later answer can use. It has four parts:

• A shared wiki: Business definitions, decisions and exceptions are stored in one place with source links and revision history.
• Corrections that stick: When someone corrects an answer, the fix can be added to the wiki so the next person does not repeat it.
• Connected business data: Context sits alongside sources such as Snowflake, Salesforce and NetSuite, so discussion can become analysis.
• Permissions that follow the person: Queries run under the asker's own access, with row-level security and column masking applied before data reaches the model.

Here is how that looks in practice:

1. The AI gets it wrong: An analyst asks why revenue declined last quarter, and the AI includes refunded transactions.
2. A colleague corrects it: A finance lead explains that revenue excludes refunds, and that correction goes into the wiki.
3. The investigation improves: The analyst reruns it with the right definition, and a tracking change from last month shows up as a likely cause because that decision was already recorded.
4. The next person benefits: When a product manager asks a similar question next week, the answer starts from the corrected version.

Before you sign anything, run a one-week trial with the five questions that cost your team the most time. Score each answer from 0 to 2 on these three points:

• Correct: Does the answer match what your best expert would say?
• Sourced: Does it cite a source you can open?
• Self-contained: Did anyone have to re-explain the context?

A tool that scores high on all three fits your team. A low score on the third point is the sign of a missing knowledge layer. If that is where your current tool falls short, explore PromptQL and start with the same five questions, or read how other teams use it in its case studies.

What Is the Difference Between a Company Brain and RAG?

RAG retrieves passages from documents to answer a question. A Company Brain also records corrections and decisions, and it resolves conflicts when sources disagree. Retrieval can sit inside a Company Brain, but retrieval alone does not build lasting team knowledge.

Should You Build or Buy a Company Brain?

Buy when access levels differ, sources conflict, data is sensitive or agents take actions. Building can work for a small, close-knit team with mostly shared access, although open-source tools still leave security and maintenance to you.

What Should You Prepare Before Switching Away From Glean?

Prepare four things before you switch. Start with a source inventory that lists every connected app and who owns it. Then confirm how your groups and access rules carry over to the new tool. Keep both tools live for a few weeks so you can compare their answers side by side. Finally, tell people where to ask questions and how to report wrong answers.

What Mistakes Should You Avoid When Setting Up a Company Brain?

The common ones are ingesting everything, skipping a feedback loop and adding permissions last. Too much unfiltered content turns the brain into noise, and without feedback it keeps using day-one beliefs. Retrofitting permissions costs more than building them in.

1. 8 Best Glean Alternatives for Engineering Teams (2026) - getunblocked.com
2. Glean alternatives: 7 best options (2026) — ToolGlance - toolglance.com
3. Glean alternatives | Tricky Wombat - www.trickywombat.ai