Ingest
Structure approved content, metadata, updates, and ownership across repositories and systems.
AI Knowledge Systems · Information Architecture
We build internal search that answers questions from your own documents.
Staff type a question in plain English and get an answer drawn from your own documents, with a link to the document it came from. It only reads what that person is already allowed to see. We build the part underneath: what it may read, who it answers for, how it cites, and when it should say it does not know.
What it is
What this is
Company Brain reads the sources you approve across Microsoft 365, SharePoint, Slack, Teams and your own systems through one controlled retrieval layer.
The underlying platforms remain sources of truth. Structured ingestion, metadata, semantic search, retrieval-augmented generation, access controls, source attribution, answer validation, and monitoring make their information usable together.
The problem
The problem this solves
It is in a Slack thread, an old deck, and the head of one person who has been there nine years.
Every tool has search. The business does not run inside one tool. So people ask a colleague, or rebuild a decision that was already made.
Architecture
How it is built
The design keeps access, retrieval, and audit controls between the source systems and the employee experience.
Company sources
Microsoft 365
Google Workspace
Slack and Teams
Notion and Confluence
Jira and project tools
Databases and file stores
Governed retrieval layer
Structured ingestionApproved connectors · parsing · metadata · update schedules · source health
Retrieval architectureKeyword and semantic search · RAG · filters · ranking · scale
Validate answersSource attribution · evidence checks · uncertainty · hallucination controls
Control and monitorUsers · groups · permissions · audit history · quality · usage
Employee experience
Ask a question
Search company knowledge
See cited sources
Check project context
Use role-specific assistants
Review usage and health
What it does
What the system does
The visible answer is only the final layer of an information system designed for trust, access, quality, and scale.
Retrieve
Use keyword search, semantic search, RAG, and filters appropriate to the question and source estate.
Validate
Attach source evidence, test difficult queries, detect weak support, and control when the system should abstain.
Govern
Enforce permissions, audit activity, monitor quality and usage, and assign accountable information owners.
Knowledge system questions
Before building an internal AI knowledge base.
How do I build an internal AI knowledge base?
Start by defining the questions employees need answered, the approved sources that contain those answers, the permissions that must be preserved, and how people will verify results. The technical design follows those operating requirements.
Can I create a private ChatGPT for my company?
Yes, but the useful version is more than a chat interface. It needs approved company sources, access controls, retrieval rules, citations, logging, source-health monitoring, and a clear process for information that should not be returned.
Can AI search Google Drive, SharePoint, Slack, or Notion?
Many document, messaging, and knowledge platforms can be connected through supported APIs or approved integration methods. The exact design depends on the platforms, account configuration, content volume, permissions, and security requirements.
How does an AI knowledge base respect employee permissions?
The system should check the requesting employee's access before retrieving or presenting information. Existing groups and source permissions can remain authoritative, with additional logging and controls added where required.
Will answers include links to the original sources?
Yes. Company Brain is designed so employees can inspect the document, message, record, or system behind an answer instead of accepting an unsupported response.
How long does it take to build a company knowledge system?
The timeline depends on the number and condition of the sources, permission complexity, required integrations, priority questions, and testing needs. A focused pilot can begin with one team or knowledge area before the system expands.