Company Knowledge Base & RAG
One source of approved answers for every AI tool you use
We set up and run a company-wide knowledge base for AI: your documents, wikis and records indexed with their permissions, kept current automatically, and available to your assistants, your applications and the AI tools your staff already use — every answer grounded in your sources and cited.
One knowledge base, many AI tools
Most organizations now have several AI tools in use — a chat assistant here, a help desk feature there, staff using Claude or ChatGPT on their own. Each sees a different slice of the company’s information, or none of it, so answers vary and can’t be trusted.
A single, governed knowledge base fixes that. Content is collected once, kept current and indexed with its access rules, and every AI tool draws on the same approved sources. You own it, and it outlasts any one AI product.
Retrieval, not guesswork
Retrieval-augmented generation (RAG) means the AI looks up the relevant passages in your documents before it answers, and answers only from those. Done well, it gives accurate, cited answers that reflect the latest version of a policy or procedure.
Doing it well is the hard part: parsing documents properly, finding the right passage among thousands, respecting permissions and measuring quality over time. That engineering is what we provide.
How it fits together
Your sources
- SharePoint & drives
- Confluence & wikis
- Help desk & CRM
- Databases & file shares
Ingestion
- Connect & syncChanges and deletions
- Parse & splitText, tables, scans
- PermissionsWho may see each item
Knowledge base
- Search indexVector and keyword
- Retrieve & rerankOnly permitted sources
- Answer & citeGrounded, with links
Used by
- Teams, Slack & intranet
- Your applications
- Claude, ChatGPT, GeminiThrough MCP
- Single sign-on
- Audit log
- Your cloud or servers
- Quality evaluation
What’s included
Connectors to your content
SharePoint and OneDrive, Google Drive, Confluence, file shares, help desk and CRM knowledge, databases — brought into one index.
Permissions kept
Each document keeps the access rules it has at the source, so people only get answers from what they’re already allowed to see.
Careful parsing
Text, tables, slides and scanned pages extracted properly — split along headings and sections, not at arbitrary lengths.
Search that finds the right passage
Vector and keyword search combined, with reranking, so policy numbers, product codes and plain-language questions all work.
Answers with sources
Every answer cites the documents it came from and links back to the original, so people can check it.
Always current
Changes, new files and deletions are picked up automatically. Retired documents stop being used the day they’re removed.
Content owners & gaps
Each collection has an owner and review dates, and a report shows the questions the knowledge base couldn’t answer.
Measured quality
A test set of real questions with known answers, run after every change to content, models or settings.
Used everywhere your people work
Teams & Slack assistant
Staff ask in the chat tool they already use and get a cited answer in seconds.
Intranet & web search
A search box that answers the question instead of returning a list of files.
Inside your applications
A simple API so your line-of-business and help desk apps can show relevant answers in context.
Claude, ChatGPT & Gemini
An MCP server lets your teams’ AI tools and agents search the knowledge base, under the same permissions.
Customer-facing assistants
A public subset — approved FAQs, product and policy pages — can power your website chatbot.
Agents & automation
Workflows that draft replies, fill forms or prepare briefings, grounded in the same approved sources.
Where it runs
In your environment, on the stack that fits your data, security rules and budget. For an isolated environment in your own cloud account, see Private AI Cloud.
Managed cloud search
Azure AI Search, Amazon Bedrock Knowledge Bases or Vertex AI Search, in your own cloud account.
Your own search stack
PostgreSQL with pgvector, OpenSearch or Elasticsearch, for full control over indexing and cost.
Fully private
Embeddings and answers computed on your servers with local models — nothing leaves your network.
How we deliver
Inventory
Map the content people ask about, where it lives, who owns it and who may see it.
Pilot
Index one collection, build a test set from real questions and measure answer quality.
Build
Connectors, permission sync, indexing pipeline and the first channels, in your cloud or on your servers.
Roll out
Add collections and channels, with content owners and review dates for each.
Improve
Review unanswered questions and quality results, and keep content and models current.
Contact us
Put your company’s knowledge to work
Tell us which content your people search for most, and we’ll show you a pilot knowledge base built on a sample of it.
- 202.747.3355
- [email protected]
- 1717 K St., N.W. Suite 900, Washington, DC 20006