6 Best AI Tools to Build a Company Brain in 2026

The best tools to build a company brain in 2026 are Glean (enterprise search across 275+ connectors, quote only), PromptQL (a shared agent whose corrections land in a team wiki, Team plan from $40 per paid user per month), Guru (a verified knowledge layer, custom pricing), Notion AI (a wiki you already write in, Business plan at $20 per member per month), Atlassian Rovo (included with Jira and Confluence Cloud, 25 to 150 credits per user per month) and Company Brain, a months-old governance product that actually carries the name and starts at $0. They are not six versions of one thing. Each is built on a different architecture, and the architecture decides what your "brain" will know, how it gets corrected and what it costs to keep alive.

That is the part most roundups skip. A company brain is a goal, not a product category with a spec. Vendors reach for it from four directions: search over the sources you already have, a wiki that people curate, a knowledge graph of how work connects, and an agent that keeps shared memory. We read each vendor's own product, pricing and security pages on 12 October 2026 and sorted the six tools by which of those four they really are.

Key takeaways

• "Company brain" describes an outcome: one place where a person or an AI agent can ask how the company works and get a sourced answer that respects permissions. Four different architectures get sold under the label.
• Glean and Atlassian Rovo are search and graph products. They index what exists. Glean lists 275+ connectors and publishes no price; Rovo comes with paid Atlassian Cloud plans and meters AI use in credits.
• Notion AI and Guru are curated knowledge bases. Notion's Business plan is $20 per member per month; Guru sells a scoped package and publishes no per-seat price.
• PromptQL is the agent-with-shared-memory option. Corrections made in a thread become reviewed wiki entries, and pricing is public: free Playground, Team from $40 per paid user per month, Enterprise from $1,000 per month.
• Two unrelated products are literally named Company Brain. The one we include, at companybrain.work, lists 8 live connectors and SOC 2 Type II as "planned". Treat it as an early bet.
• We did not run hands-on tests. Everything here comes from vendor pages, and the ranking is a judgement about fit.

What a company brain is, and what it is not

A company brain is a shared, permission-aware store of what an organisation knows (its decisions, definitions, policies and the reasons behind them) that both people and AI agents can query and get a cited answer from. The phrase took off in 2026. PromptQL's blog says the framing comes from Y Combinator's Summer 2026 Requests for Startups; we could not load that entry from YC's own page, so take the attribution as PromptQL's.

The need behind it is older than the name. A Panopto survey reported by HR Dive in July 2018 found knowledge workers spending 5.3 hours a week waiting on colleagues for information or recreating work that already existed. The figure is eight years old and comes from a vendor's own study, so read it as a rough indication of scale.

What separates a brain from a search box is what happens after a wrong answer. In a search product, someone has to find and fix the source document. In a brain, the correction itself should be captured, reviewed and served to the next person who asks. Few products do all of that.

A company brain is also not the same job as documenting tribal knowledge. Recording a process so it exists in writing is the capture problem. This article is about the layer that answers questions afterwards.

The four architectures behind a company brain

Enterprise search over existing sources

The tool connects to your apps, indexes their content and mirrors each app's permissions. Nothing has to be rewritten. Coverage on day one is the selling point, and quality is capped by what the sources already say. If three documents disagree about the refund policy, search finds all three.

A curated wiki

People write pages, and AI answers from them. Accuracy can be high because a human decided what is true, but the brain only knows what somebody bothered to write down, and pages go stale unless there is a verification routine.

A knowledge graph

Instead of only indexing text, the system models entities (people, projects, customers, tickets) and the links between them, so it can answer questions that need several hops. Glean calls its version the Enterprise Graph and Atlassian calls its version the Teamwork Graph. In both cases the graph is inferred for you from activity in connected apps. If you want to build a graph yourself, our guide to AI tools for building a knowledge graph covers that route.

An agent with shared memory

Here the brain is a by-product of work. A team uses an AI agent in shared threads, somebody corrects it, and the correction is saved as knowledge every later session starts from. This is the newest of the four and the least proven at scale.

The six tools at a glance

Tool	Architecture	Where knowledge lives	Public starting price	Published certifications
Glean	Enterprise search plus knowledge graph	Index of connected apps, in a single-tenant environment	Not published	SOC 2 Type II, ISO 27001, ISO 42001
PromptQL	Agent with shared memory	Team wiki (knowledge, skills, semantic layer)	$0 Playground; Team from $40 per paid user per month	SOC 2 Type II, ISO 27001, HIPAA, GDPR, CCPA
Guru	Curated, verified knowledge layer	Guru knowledge base, delivered to other tools	Not published	SOC 2 Type II, HIPAA, GxP
Notion AI	Curated wiki plus search	Notion pages and connected apps	Business at $20 per member per month	SOC 2 Type 2, ISO 27001
Atlassian Rovo	Knowledge graph plus search	Jira, Confluence and connected apps	Included with paid Atlassian Cloud plans	Not checked for this article
Company Brain	Governed knowledge for agents	Approved "facts" and "skills"	$0; paid plans from $20 per month per organisation	None yet (ISO 27001 and SOC 2 Type II planned)

Certifications are as each vendor lists them on its own site. We did not open any audit report, and a badge tells you nothing about which product modules or hosting options are in scope. Ask for the report.

How we evaluated

We scored each tool on five questions, using only what the vendor publishes about itself.

1. Reach: how much existing company knowledge can it see without anyone rewriting it?
2. Correction loop: when an answer is wrong, does the fix reach everyone, and does a human approve it?
3. Permissions: whose access does an answer run under?
4. Live data: can it compute a number from a database, or only find a document that mentions the number?
5. Price transparency: can a buyer work out the cost before a sales call?

The order below weights reach and the correction loop most heavily, because those two decide whether the thing behaves like a brain or like a search bar. A team whose knowledge all sits in Confluence would reasonably put Rovo first. No tool was benchmarked.

The 6 best AI tools to build a company brain

1. Glean: the widest reach across existing sources

Glean is the search-first answer, and for a large company with knowledge spread over dozens of SaaS tools it is the most direct one. Its connectors page counts 275+ native and MCP-based connectors (the site navigation still says "more than 250"). Permissions are inherited from each source, and Glean says permission changes are "reflected immediately in results".

On top of the index sits the Enterprise Graph, which maps relationships between people, projects, customers and documents and also builds a personal graph per employee. Glean says it constructs the graph with machine learning inside each customer's single-tenant environment. Agents can act in connected systems, with approval steps you can require before anything runs. The security page lists SOC 2 Type II, ISO 27001 and ISO 42001.

What to consider:

• No public pricing. The pricing URL redirects to the homepage, so budget for a sales process.
• A wrong answer usually traces to a wrong or duplicated source document, and that document still has to be fixed where it lives. Glean's platform page mentions "enterprise memory" that learns continuously, but we could not find published detail on how a correction is reviewed or shared across users.
• Reach is only useful if the sources are worth reaching. Messy drives produce messy answers.

Best for enterprises that need permission-aware search over a sprawling stack before anything else. If Glean's quote or scope does not fit, we compared Glean alternatives separately.

2. PromptQL: an agent that writes its corrections into a team wiki

PromptQL, made by Hasura, approaches the problem from the other end. It is an AI workspace where a team shares a bot, and the brain is what accumulates as people correct it. Its shared context page shows the mechanism: after a correction, the bot proposes a wiki entry, a person reviews or edits it and clicks "Add to wiki", and later sessions start from that entry. The wiki keeps revision history, audit trails and change notifications, and it can be split into scopes (customer, internal, personal, confidential) so different people see different parts.

PromptQL does use the brain language. Its Tag page says the product "builds your company's shared brain as you work", and its blog published a how-to on building a company brain in August 2026. The same page states that the agent "acts with the triggering user's permissions" and that row-level and column-level access is enforced at the data layer. Because it connects to databases such as Snowflake, Postgres and BigQuery, it can calculate a figure and not just retrieve a page about it.

Pricing is the most open in this list. The pricing page shows a free Playground, a Team plan that starts at $40 per paid user per month (every user starts free, and paid usage is added in $40 increments, billed weekly), and Enterprise from $1,000 per month, consumption based with a monthly minimum and single-tenant deployment. Bring-your-own-cloud and self-hosting are contract priced. Its security page lists SOC 2 Type II, ISO 27001, HIPAA, GDPR and CCPA.

What to consider:

• It starts with little. A search product knows your whole drive on day one; this kind of brain is only as good as the corrections your team has fed it, though PromptQL says it can seed a wiki from Slack, docs and warehouse tables.
• Usage is metered in the vendor's own units, and the pricing page says the model you choose "changes your mileage". A heavy user on a frontier model will cost more than $40 a month, and you cannot tell how much more from the page.
• Salesforce is absent from the public integrations catalog (HubSpot, Attio, Pipedrive and NetSuite are listed), even though a demo animation on the shared context page shows a Salesforce source. PromptQL says it can connect to any database or API on request, so ask for a working demo against your CRM.
• Chat surfaces are narrower than they look. The architecture page names Slack and Teams. The Tag page also shows WhatsApp and Discord labels, but the only launch note on it is for Microsoft Teams, so confirm availability.
• We found no independent accuracy benchmark, and the usage statistics on its site come from PromptQL's own 70-person team.

Best for data, finance, operations and go-to-market teams whose repeat questions mix business definitions with live numbers, and who will actually review the suggested wiki edits.

3. Guru: a verified layer that feeds your other AI tools

Guru now describes itself as "the governed knowledge layer for enterprise AI", and the pitch is that it sits underneath whatever assistants you already use. The features page lists expert review workflows that route content to the right owner on a schedule, detection of redundant and conflicting content across sources, and flagging and archiving of stale content. Guru claims its automation handles roughly 80 to 90% of verification from usage signals, content age and policy rules, with experts pulled in for the rest. That is the vendor's number and we could not test it.

Delivery is broad: Slack, Microsoft Teams, a browser extension, and MCP so other AI tools can pull governed answers with the same permissions and citations. Guru says one correction propagates to every connected surface. The pricing page lists 100+ integrations, SOC 2 Type II, HIPAA and GxP, plus SSO, SCIM, role-based access and DLP masking.

What to consider:

• There is no price. Guru says it is "not just a per-seat tool" and sells a package that bundles the platform with a team of solution engineers, scoped on a sales call.
• A verified layer needs owners. If nobody in the business will accept being the named expert for a topic, the verification queue becomes the new stale wiki.
• It answers from governed knowledge and documents. We saw nothing about computing answers from a warehouse.

Best for support, sales and enablement teams that answer the same policy and product questions all day and need a defensible, expert-approved answer in several tools at once.

4. Notion AI: the brain you get if your wiki is already in Notion

For a team whose handbook, specs and meeting notes live in Notion, Notion AI is the shortest path. The pricing page lists Free at $0, Plus at $10 and Business at $20 per member per month, and says yearly billing saves up to 20%, so check which billing mode a quote uses. Free and Plus get only a trial of Notion AI. Business adds Notion Agent, AI meeting notes, page verification and Enterprise Search, which the plan card still labels beta.

Enterprise Search extends answers beyond Notion to Slack, Google Drive, GitHub, Jira, Microsoft Teams, SharePoint and OneDrive. Notion's security documentation says permissions are checked at query time and that changes in a source system are reflected within one hour, longer for large workspaces. That is slower than Glean's claim, and it matters if you revoke access often. Verified pages carry a badge that appears in search results and AI citations. Custom Agents cost $10 per 1,000 Notion credits after a free trial.

What to consider:

• Zero data retention with Notion's LLM providers applies to the Enterprise plan. The comparison table shows 30-day retention on the other plans.
• The brain is as current as the pages. Verification is a manual badge; we found no automated routine that routes stale pages to an owner the way Guru describes.
• Connector coverage is a short list next to Glean's, and the pricing page marks several (Jira, Box, OneDrive, Salesforce, Asana) as beta.

Best for small and mid-size teams that already treat Notion as the source of truth. For other wiki-first options, see our comparison of AI-powered wiki tools.

5. Atlassian Rovo: a work graph for teams on Jira and Confluence

Rovo is Atlassian's search, chat and agent layer, built on the Teamwork Graph, which Atlassian calls "the context layer for intelligent organizations". If your decisions are recorded in Confluence and your work in Jira, much of your company brain is already in that graph.

The commercial model is unusual. Rovo is available to customers on a Standard, Premium or Enterprise Cloud plan of Jira, Confluence, Service Collection or Teamwork Collection, at no separate licence fee. AI usage is metered in credits. Atlassian's licensing page gives the monthly allowance for Jira and Confluence as 25 credits per user on Standard, 70 on Premium and 150 on Enterprise, pooled across the organisation and stacked across apps. Its own example: 100 Premium users on both Jira and Confluence get 14,000 credits a month. A basic AI interaction costs 10 credits, so that Standard allowance is small. When credits run out, new AI requests pause until the next month unless you buy more, though Rovo Search inside Atlassian apps keeps working.

What to consider:

• Cloud only for the full product. Atlassian states that Search, Chat, Agents and Studio need a Cloud plan; Data Center customers get connectors that sync Jira and Confluence content to the cloud, not a self-managed Rovo.
• 25 credits per user per month on Standard works out to two or three basic AI interactions each, before pooling. Model your real usage before assuming Rovo is free.
• It is strongest on Atlassian content. We did not verify the current number of third-party connectors, so check the connector list against your stack.
• Corrections happen in the source: you edit the page or the issue.

Best for engineering and product organisations already standardised on Atlassian Cloud.

6. Company Brain: the product that carries the name, and is very new

Two unrelated products are called Company Brain, and the draft material we started from blended them into one. They should be kept apart.

The one we rank is at companybrain.work. It describes itself as "knowledge governance for AI agents" and says it is built in Johannesburg. Its idea is narrow: before an agent uses a policy, a named person must have approved it, and when the source changes, every answer that depended on it is flagged until a correction is approved. The platform page describes a six-stage pipeline (connect, extract, curate, publish, watch, expose) and delivers knowledge to agents through an MCP gateway and REST API.

Pricing is per organisation, with unlimited readers: Free at $0 (100 facts, 1 curator, 2 connected sources), Plus at $20 a month, Pro at $100, Team at $200, and a quote-only Enterprise track with self-hosting, SSO and SCIM.

What to consider:

• It is early, and the vendor says so. The platform page counts connectors as "8 live, 4 in progress, 116 planned". The assurance page puts ISO 27001, SOC 2 Type II and an independent penetration test under "planned", after "the first production cohort". The homepage invites design customers.
• The domain was registered in August 2026, according to the WHOIS record we pulled. We found no named customers.
• It governs knowledge that agents consume. It is not an employee-facing search or chat product in the way the other five are.

The second product, CompanyBrain at companybrainai.com, is aimed at owner-run businesses and promises to capture what lives in the owner's head so the business can run, or be sold, without them. We found no public pricing page for it, and the margin and response-time figures on its homepage sit inside a product demo widget. They are illustrations, and we have left them out.

Best for a regulated team that wants to pilot approval-gated knowledge for agents on the free tier and accepts the risk of a young vendor.

Which architecture fits which problem

If your situation is	Architecture to start with	Tools from this list
Knowledge exists but is scattered over many apps	Enterprise search	Glean; Rovo if most of it is in Atlassian
Knowledge exists in one well-kept workspace	Curated wiki	Notion AI
Answers must be expert-approved and identical in every tool	Verified knowledge layer	Guru; Company Brain for a pilot
Questions need several hops across people, projects and tickets	Knowledge graph	Glean, Rovo
The knowledge is in people's heads and comes out as corrections	Agent with shared memory	PromptQL
Questions need a number computed from live data	Agent with database access	PromptQL

Pairing two is common and sensible. Search and a curated layer solve different halves: one finds what was written, the other settles what is true.

One practical test before any purchase. Pull the 20 questions your team asked most often last month and sort them: could a document answer this, does it need a definition someone has to rule on, or does it need a query? The split tells you which architecture you are short of. New hires are a good source for that list, and our piece on AI tools for employee onboarding looks at that use case on its own.

Limitations

This comparison rests on vendor-published pages read on 12 October 2026. Specific gaps:

• No product was tested hands-on. Answer quality, latency and setup effort are not assessed.
• Certification claims are as listed on vendor sites. We did not obtain audit reports or check scope. Atlassian's certifications were not reviewed.
• Glean and Guru publish no prices, so we cannot compare total cost. PromptQL's and Rovo's real cost depends on usage units we could not model.
• Notion's page did not make clear to us whether $20 is the monthly or yearly-billed rate.
• We could not read the Y Combinator Summer 2026 request that reportedly popularised the term, because YC's page served only its Fall 2026 list to us.
• Guru's 80 to 90% automated verification figure and Glean's "immediately" for permission sync are vendor statements.
• Company Brain's age is inferred from a WHOIS record and its own "planned" labels. We did not speak to the company.
• Rovo's third-party connector count and PromptQL's WhatsApp and Discord availability were not confirmed.

Frequently asked questions

What is a company brain?

A company brain is a shared store of an organisation's decisions, definitions and policies that people and AI agents can query for a cited, permission-aware answer. It differs from plain search because it is expected to hold corrections and context, not only documents.

Is a company brain just RAG?

No. Retrieval-augmented generation is one technique a company brain may use to pull documents into an answer. A working brain also needs permission enforcement, a way to capture and review corrections, source tracking, and often the ability to query structured data.

Which tool is cheapest to start with?

On published prices, Company Brain and PromptQL both have $0 tiers, Notion's Business plan is $20 per member per month, and Rovo adds no licence fee if you already pay for Atlassian Cloud at Standard or above. Glean and Guru require a quote. Free tiers are limited: Company Brain's allows 100 facts and one curator.

Can a small business build a company brain?

Yes, and a small business should probably not start with enterprise search. A team of 20 with its docs in Notion gets most of the way on the Business plan. A team whose knowledge is mostly unwritten will get more from an agent it corrects as it works, or from simply writing the top 20 answers down first.

Do these tools train AI models on our data?

Notion says its contracts with AI providers prohibit training on customer data, and Guru's pricing page says "your data never trains our AI models". We did not find or check an equivalent statement for every vendor here. Ask each one for its data processing agreement, and confirm retention terms for your plan, since Notion's zero retention applies only to Enterprise.

How long does it take to get useful answers?

Search products answer as soon as connectors finish indexing; Notion documents an initial 36-hour sync period for Enterprise Search. Curated and agent-memory products take longer to become reliable, because they depend on people verifying pages or correcting answers. Nobody publishes a credible number for that.

How is this different from ChatGPT Enterprise or Microsoft Copilot?

Those are general assistants that can connect to company apps. The tools here are built around a shared knowledge layer, whether indexed, curated or learned. Guru and Company Brain both sell themselves as a governed source that other assistants read through MCP.

Conclusion

Pick the architecture before the vendor. If the knowledge is written down and scattered, Glean (or Rovo inside Atlassian) reaches it. If it is written down in one place, Notion AI is enough. If it has to be signed off, Guru is the established choice and Company Brain an early one. If it mostly lives in people's heads and surfaces as corrections, or the questions need live numbers, PromptQL is the tool in this list built for that, with the caveat that it starts with little and learns only as fast as your team teaches it.

Whichever you choose, the first month's work is the same and no vendor does it for you: decide who rules on each disputed definition.