Ask your own business a question, get a real answer
An internal knowledge base puts everything your business knows in one place your team can actually ask. We ingest your documents, contracts, procedures, and past projects into a private retrieval system, so anyone gets a sourced answer in plain language in seconds, instead of hunting through folders or interrupting the one person who remembers.
What is standing still costing you?
Everything your business has learned sits in folders, inboxes, and one or two people’s heads, which is exactly where it stays when they are busy or gone.
We build a private knowledge base over your own documents, so anyone can ask a plain question and get an answer with its source attached.
How does it work?
01 Find where your knowledge actually lives
On a free consult we map it: the shared drive, the email threads, the contracts, the procedures nobody wrote down, and the two people everyone asks. That map is the difference between a knowledge base and another folder.
02 Ingest it, without moving it
We connect to the systems you already keep things in and index what is there. Your files stay where they are, in your own accounts, and nothing is uploaded to train somebody else’s model.
03 Build the retrieval layer
This is the part that matters. A retrieval-augmented system finds the passages that actually bear on your question and answers from those, rather than from whatever a general model has absorbed about businesses in general.
04 Make every answer traceable
Each answer arrives with the documents it came from, so it can be checked in one click. An answer you cannot verify is worse than no answer, because someone will act on it.
05 Set who can see what
Permissions follow your existing ones. The knowledge base should not become the place where the whole company can suddenly read payroll, and it does not.
06 Keep it current as you work
New documents are picked up as they land, so the answers reflect this quarter rather than the day we finished. A knowledge base that goes stale gets abandoned within a month.
What do you get?
- A private knowledge base built over your own documents and systems
- Plain-language questions, with answers in seconds
- Every answer sourced, showing the documents it came from
- Permissions that match the access people already have
- Automatic updating as new documents and decisions land
- Your data staying in your accounts, not training an outside model
What is an internal knowledge base?
It is a single place your team can ask instead of search. Everything the business has written down, contracts, quotes, procedures, project histories, supplier terms, gets indexed into one private system, and anyone can ask it a question in plain language and get an answer back in seconds with its sources attached.
The point is not storage. You already have storage, and that is the problem: the answer exists, in a folder nobody thinks to open, in a thread from two years ago, or in the head of the person who is on holiday.
How is this different from ChatGPT?
A general model knows the public internet. It does not know your pricing rules, your last three contracts with a supplier, or why you stopped doing something a certain way in 2023. Ask it about your business and it will produce something plausible, which is the worst possible failure mode.
This is built with retrieval-augmented generation. The system first finds the passages in your own documents that bear on the question, then answers from those and shows you which ones. When your documents do not contain the answer, it says so rather than filling the gap.
What does it cost you to leave knowledge where it is?
Every business runs on things only a few people know, and that arrangement works until it does not. Somebody is off, somebody leaves, or somebody is simply interrupted for the fourth time that day to answer a question that was already answered in writing a year ago.
The compounding cost is the decisions made without the answer, because finding it would have taken an afternoon and the meeting was in ten minutes.
What can your team ask it?
The questions that currently get asked in person, or not at all:
- What did we quote this client last time, and what did we include?
- What is our actual policy on returns, deposits, or cancellations?
- How do we onboard a new supplier, and who signs off?
- What went wrong on the last project like this one?
- Which of our contracts renew this quarter, and on what terms?
Where does our data go?
It stays in your accounts. The knowledge base is built over your own storage with your own permissions, and your documents are not used to train anyone else’s model. Where a model is called, it is called on the passages needed to answer one question, not handed your corpus.
Can customers use it too?
The same retrieval layer can face outward, answering customer questions on your site from the subset of material you choose to expose. That was the old chatbot service, and it is now one thing this can do rather than the whole of it. Inward is usually where the bigger return sits, because that is where the knowledge is.
Internal Knowledge Base: frequently asked questions
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What is an internal knowledge base?
- It is a private system built over everything your business has written down: contracts, quotes, procedures, project histories, supplier terms. Your team asks it a question in plain language and gets an answer in seconds with the documents it came from, instead of searching folders or interrupting the person who remembers.
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How is this different from just using ChatGPT?
- A general model knows the public internet, not your pricing rules or your last three contracts with a supplier. Ask it about your business and it produces something plausible, which is the worst failure mode there is. This is retrieval-augmented: it finds the passages in your own documents that bear on the question, answers from those, shows you which ones, and says so when the answer is not there.
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Where does our data go, and is it used to train anything?
- Your documents stay in your own accounts and are not used to train anyone else’s model. The knowledge base is built over your existing storage and inherits your existing permissions, so the people who could not read a file before still cannot. Where a model is called, it is called on the passages needed to answer one question.
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Does it stay up to date?
- Yes. New documents are picked up as they land, so answers reflect how the business works now rather than the week we finished. This matters more than it sounds: a knowledge base that goes stale is abandoned within a month, and then it is just another folder.
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Can it answer customer questions on our website too?
- It can. The same retrieval layer can face outward and answer from the subset of material you choose to expose, which is what a website chatbot is. Inward is usually where the bigger return sits, because that is where the knowledge that is hardest to reach actually lives.