Build a
Company Brain
your AI can read
At £10m+ turnover, company knowledge is usually split across departments, document stores and experienced people. We bring the useful parts together with permissions, sources and an owner for every answer.
20%
OF THE WORKWEEK LOOKING FOR INFO
42%
INSTITUTIONAL KNOWLEDGE UNIQUE TO ONE PERSON
Cited answers
FROM APPROVED SOURCES
AI needs access to trusted company knowledge
A general AI service does not know your pricing, customers, bid history, supplier decisions or the exception a senior manager applies in a specific case.
Knowledge exists, but it's spread across tools, tickets, files and people. McKinsey estimated that interaction workers spend nearly 20% of the workweek looking for internal information or tracking down colleagues who can help. Panopto found 42% of institutional knowledge is unique to individual employees.
WHERE IT LIVES NOW
- In one or two people's heads
- Slack threads that are hard to find
- Email chains, attachments, PDFs
- A Notion that isn't current
- Spreadsheets named "Final_v8"
A COMPANY BRAIN
- One indexed memory across all of it
- Answers cited back to the source
- Respects who's allowed to see what
- Updated as the business changes
- Search like Google, ask like ChatGPT
What a useful company brain needs
The technical options include retrieval-augmented generation, vector search and knowledge graphs. The right design depends on the sources, permissions, update frequency and answers people need.
Sources
Slack, Raq.com, Gmail or Outlook, Notion, Confluence, Google Drive, SharePoint, your CRM, your spreadsheets, your internal apps. Plus the bits in people's heads.
Ingest
Pipelines that pull from each source, clean it, chunk it, tag it with who, when and where. New documents picked up automatically.
Memory
A vector store for meaning, a structured store for facts, a graph for relationships. Your data, encrypted, hosted where your contracts require, with model access controlled.
Retrieval
The bit that finds the right two paragraphs from the right document at the right time. Tuned per use case, so the AI gets fed enough context (not a haystack).
Trust layer
Permissions that match your org. Every answer cites its source. Every query logged. Sensitive material flagged and walled off. Auditors can see what was asked and who saw it.
Capture spoken knowledge
A habit worth starting before you build anything else.
A lot of what your company knows never gets stored. It comes out in meetings, client calls, standups, the quick debrief after a site visit, the decision someone explains once and never writes up.
Get in the habit of recording those conversations and running them through transcription. A searchable transcript is the cheapest new source you can add, and a company brain can only index what has been captured.
Record as much as you reasonably can. Transcribe it. Store it where the rest of your knowledge lives.
What the leadership team gets
Asking staff to document everything from scratch rarely works. We start with existing material and use short structured interviews to fill important gaps.
Each phase covers named sources, user groups and permissions. Your team tests the answers and citations before another department or document set is added.
BOOK AN ADVISORY CALLKnowledge audit
We map what your company knows and where each bit lives. Sources, owners, sensitivity. You get a one-page picture of your real knowledge base before we build anything.
Build the brain
Connectors, ingest, vector and structured memory, retrieval, permissions, logs.
Wire up the first answers
The first release covers a defined user group, approved sources and one useful workflow such as bid research, support drafting or onboarding.
Keep it fresh
Checks can flag stale, contradictory or missing knowledge for an owner. Approved changes are recorded and tested before they become part of the source used by other workflows.
Evidence behind company knowledge systems
A few numbers worth keeping in mind when you're deciding what to build.
Nearly a day a week, gone.
McKinsey estimated that interaction workers spend nearly 20% of the workweek looking for internal information or finding colleagues who can help. A searchable internal record can cut that search time by up to 35%.
42% lives in one head.
Panopto's workplace report found 42% of institutional knowledge is unique to individual employees and isn't shared with coworkers. Every leaver takes a slice of the operation with them.
Agents have arrived.
Gartner expects up to 40% of enterprise applications to include task-specific AI agents by the end of 2026, up from less than 5% in 2025. Useful agents need useful business memory.
Sources: McKinsey Global Institute, "The Social Economy" (2012); Panopto Workplace Knowledge and Productivity Report (2018); Gartner press release "40% of Enterprise Apps Will Feature Task-Specific AI Agents by 2026" (Aug 2025).
Raq.com Company Knowledge is built for this job
Our own companies use shared knowledge with account permissions and connected tools. Answers can sit beside the work while the source material, access and ownership remain visible.
When this is worth discussing
We work best when there is a real operating problem, enough volume to measure and people from the affected teams who can make decisions.
Usually a good fit
- An established UK business, usually with annual revenue above £10m
- A repeated process with a known cost, delay, error rate or capacity problem
- A senior sponsor and a day-to-day owner who understand the work
- Access to the relevant staff, systems, sample records and security requirements
We may point you elsewhere
- A standard product already covers the process well
- The requirement is a one-off small build with no wider operating case
- There is no owner or access to the people and data needed to test the result
- The plan relies on AI making high-impact decisions with nobody responsible for review
Questions before committing
Isn't this just a wiki?
A wiki needs humans to write things down (good luck). A company brain reads what's already there (in Slack, email, Notion, Drive, your apps) and indexes it for both people and AI.
Can't we just point ChatGPT or Copilot at our files?
You can, and for one team's drive it's often enough. The wheels come off when permissions matter, sources span tools, answers need citations, and the data can't leave the country.
How do you stop it making things up?
Retrieval first is the best way. The AI doesn't answer until it's pulled the actual passages from your company brain, and every claim links back to its source. If the brain doesn't know, the answer says so. We evaluate this on private test sets.
Who can see what?
The brain inherits permissions from the source. If you can't see a Slack channel or a Drive folder, your queries don't surface it. We wire it to your SSO (Google, Microsoft, Okta) so leavers lose access when your identity provider removes them.
Where does our data sit?
On infrastructure you own (Hetzner, AWS London, Google Cloud London, or your existing tenancy). LLM calls are configured so prompts and retrieved context aren't used for provider training. We can run the LLM call against UK or EU endpoints if your contracts require it.
What about GDPR and the ICO?
We document a record of processing activities, set up retention and deletion to match your policy, and respect subject access and erasure requests at the brain level. If you need a DPIA we'll write it with you.
How long, how much?
We scope discovery separately, then propose a first release around approved sources and a defined user group. Timing and price depend on access rules, source quality and the workflow being supported.
What if our knowledge is mostly in one or two people?
Structured interviews can capture examples and exceptions that are missing from documents. The resulting material still needs an owner, access rules and approval before it becomes a source used by the system.
Talk to us about your company knowledge
Tell us which questions still depend on finding the right person. We will map the sources, access rules and first group of users before recommending a knowledge system.