Enterprise RAG
KnowledgeCoreEnterprise RAG that turns your documents and data into instant, accurate answers.
KnowledgeCore is an enterprise RAG system. It reads everything your business has written down and answers questions about it in plain English, showing the passage each answer came from so anyone can check it.
The problem
The answer exists. Nobody can find it.
The information is not missing. It is in a policy document from 2019, in a supplier contract, in a spreadsheet on somebody’s drive, and in the head of the person who is on leave this week.
So people guess, or they ask the one colleague who always knows, or they give the customer the answer that was true last year. Search does not fix it, because search finds documents and what people need is answers.
A filing cabinet goes in.An answer comes out.
What it does
What the enterprise RAG system does
Answers the question, not the keyword
Somebody asks whether a customer in Ireland can return an item after forty days, and gets the answer — rather than eleven documents with the word returns in them.
Shows its working
Every answer arrives with the passage and the document behind it. Where it cannot find grounds for an answer it says so, instead of producing a confident invention.
Reads what you already have
PDFs, Word files, SharePoint, Confluence, Notion, a database, a shared drive full of scans. You do not have to rewrite your knowledge into a new system first.
Respects who may see what
Answers are drawn only from documents the person asking is allowed to open, so an internal margin sheet never surfaces in a customer-facing reply.
How it works
How an answer gets built
Point it at the sources
We connect the systems your documents actually live in and agree what is authoritative — because most businesses hold three versions of the same policy and only one of them is current.
Break the documents into retrievable pieces
A two-hundred-page manual is useless as one lump. It is split along its own structure, so a retrieved passage arrives carrying the heading and context it sat under.
Ground every answer in what was retrieved
The system finds candidate passages first and writes the answer only from those. The citation is not decoration — it is the mechanism that stops it making things up.
Keep it current
Documents change. The index follows them, and superseded material is retired, so the system stops quoting last year's handbook the week the new one lands.
Where it fits
Where the answer is buried
Insurance broking
Which policy covers this, up to what limit, with which exclusions. The answer is in the wording, and the wording runs to ninety pages.
Manufacturing and field service
An engineer on site needs the torque setting for one part on one machine, from a manual that exists as a scanned PDF.
Professional services
Precedent, past advice and the firm's own templates, findable by someone junior without interrupting a partner.
Internal HR and operations
The questions a team asks constantly and a staff handbook answers badly — leave, expenses, notice periods, who signs off what.
What you get
A system your team can check
A working answer system
Deployed where people will actually use it: a web app, Slack or Teams, or behind a tool they already have open.
Connectors to your sources
Live connections to the systems your documents live in, with permissions honoured and a defined refresh cycle.
An honest accuracy picture
We build an evaluation set from your own real questions and show you where it does well and where it does not. Numbers on your material, not a benchmark on somebody else's.
Handover and a support window
Documentation, a walkthrough for whoever maintains the sources, and a tuning period after launch.
Often built alongside
- ExtractIQDocument extraction
When the knowledge is trapped in scans and forms rather than clean documents, ExtractIQ pulls the structure out first, so there is something worth indexing.
- ChatCoreConversational AI
The retrieval layer that makes a customer-facing assistant trustworthy — answers come from your documents rather than the model's imagination.
Tell us what your team keeps having to look up.
The questions that come round every week, and where the answers currently live. If retrieval is the right answer we will show you how we would ground it — and if the real problem is that your documents contradict each other, we will say so.