Staff ask the same internal questions repeatedly
Experienced colleagues become the search engine for policies, processes, products and prior decisions.
Private AI assistant for company documents
Give your team answers from company documents.
We build private internal assistants that help authorised staff find answers across policies, manuals, process notes, product information and the company's own records.
Tell us what people keep asking and where the answer lives today.
In short
Can we build an in-house ChatGPT for company documents?
Yes. The usual approach connects an AI model to a chosen set of company documents, retrieves the most relevant passages for each question and returns an answer with source references. Access, retention, testing and escalation should reflect the sensitivity of the information and the decisions being supported.
Company knowledge
Why people cannot find the answer
Search returns files rather than answers
People still need to open several documents and decide which section is current and relevant.
Onboarding depends on who is available
New starters receive inconsistent explanations and take longer to navigate the company's working knowledge.
Public AI tools create uncertainty
Staff want help, but the business has not defined which tools they can use, what information stays out or who is responsible.
The assistant
What it needs to do
Answers with sources
Return a direct answer alongside links or references to the passages used to produce it.
Permission-aware retrieval
Limit available information by role, team or existing document permissions where the chosen systems support it.
Teams, web or existing workspace
Provide access through an interface that fits how staff already work rather than creating another isolated tool.
Evaluation and feedback
Test questions from real staff, record weak answers and give content owners a way to improve the source material.
Where we would start
Prove value with one document set
We start with one document set and a small user group, then test the assistant against questions the team already asks.
Typical outputs
- Document and permission assessment
- Questions from the team
- Working private assistant pilot
- Evaluation, risk and rollout plan
How it works
We start small and prove it works
A first project should earn the next one.
- 01
Understand the work
Map the current process, information, exceptions, cost and desired result.
- 02
Test what matters
Build with real examples from your own work and compare the result with how the job is done today.
- 03
Put it into use
Integrate, document, train and measure only when the evidence supports it.
Common questions
Questions about company documents
Does the model need to be fine-tuned on our documents?
Usually not simply to answer factual questions from changing documents. We normally start by retrieving the relevant source documents. Fine-tuning makes sense when a specialist task, format or consistent behaviour justifies it.
Will answers include sources?
They should. Source references make answers easier to check and help users distinguish company material from a general model response.
Can it respect existing document permissions?
Potentially, depending on the document platform and architecture. Permission behaviour must be tested rather than assumed.
Can it run without sending information to a public consumer chatbot?
Yes. There are several managed, private-cloud and self-hosted routes. The right choice depends on information sensitivity, budget, performance and support requirements.
What if our documents are outdated or contradictory?
The pilot should expose those problems. An assistant cannot make weak source material authoritative, so document ownership and maintenance are part of the design.
Get in touch
Tell us what your team keeps looking up.
Tell us which questions keep coming up and which documents contain the answers. We can help you work out whether a private assistant is the right answer.
Email us