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An enterprise LLM assistant is an AI assistant that answers staff questions, asked in plain language, from your own procedures, manuals and contracts. Using RAG, it first finds the relevant passage, bases its answer on it and cites the source. Users only get answers from documents they are allowed to see, and it can run on your own servers.
Someone answers the same question every day. Procedures, technical manuals, contracts and quality documents sit in shared folders, but finding the right one usually means finding the person who knows where it is. New starters don't know whom to ask, experienced staff field the same questions over and over, and sales or service teams keep customers waiting while they dig for information.
We set up an AI assistant that works over your own documents, so your people ask instead of trawling through folders. A maintenance technician on the floor might ask, "Which parts are replaced at this pump's scheduled service?"; the assistant finds the relevant section of the manual, answers in a few short steps and shows which document and section it used. New starters learn the leave procedure without ringing HR, and experienced staff get back to their own work instead of answering the same question again. Because every answer rests only on the passage it found (RAG, Retrieval-Augmented Generation), any reply can be checked against the original.
Procedures, manuals, contracts and training material become a searchable knowledge base. PDF, Word, Excel and scanned paperwork are all processed.
Every reply shows which section of which document it drew on. Users open the source in one click, and if the answer isn't there, the assistant says so.
The assistant answers only from documents the person asking is entitled to see, so HR, finance and board material stays with the right people.
Available through a web interface, your intranet, WhatsApp or your existing helpdesk, so nobody has to learn yet another tool.
Using open-source language models, the whole assistant can run on-premise. No data goes to an outside service, which suits organisations that cannot let data leave the building.
Top topics and unanswered questions are reported, showing which procedures are missing or out of date.
If the assistant will face your customers, see NLP & chatbots. If you would rather start with a ready-made product than a custom build, SmartFiles from the Smart360 family needs no installation: it gathers files into department and project areas, summarises each uploaded document with AI, lets you ask questions of a single document or a whole folder, and answers only from files the user is allowed to see. You can buy SmartFiles now.
We agree which documents feed the assistant, who will use it and which types of question it must handle.
Documents are split into passages and indexed in a vector database; scanned records go through OCR and access rules are defined.
We test with questions your people actually ask, review wrong or incomplete answers and tune retrieval and response settings.
The assistant goes live on its channels and usage is tracked. New documents are added to the knowledge base automatically.
Language models can sound convincing even when they don't know. By requiring a citation for every answer, we tie the assistant to your documents: if the answer isn't there, it doesn't guess, it says so, and the question lands in the gap report.
For more detail, read our guides on what RAG is and how an enterprise LLM answers from your documents, permission-aware AI assistants that prevent data leaks and reducing AI hallucinations. More articles are collected in our AI guides for business.
Will our documents leave the building? They don't have to. Using open-source language models, the assistant can run entirely on your own servers; if you prefer a cloud-based model, we agree at proposal stage which data is processed where.
Our documents are scattered, and some are scans. Most projects start that way. The first step is a document inventory: scans go through OCR, and we weed out outdated or duplicate files with you at that stage.
Who keeps it up to date afterwards? New documents are added to the knowledge base automatically, and the unanswered-questions report shows which documents are missing. Technical support is available 24/7.
Bring a handful of the questions your team asks most, along with the documents behind them, and we will walk through how the assistant would handle them. Book a call or ring 0850 346 41 09.
An AI assistant that answers staff questions, asked in plain language, from your own procedures, manuals and contracts. Every answer shows which part of which document it is based on. Common uses include HR policies, technical service manuals, quality procedures, product information for sales teams and onboarding new staff.
RAG (Retrieval-Augmented Generation) means the assistant first finds the passage that contains the answer, then bases its reply only on that passage. Because it must cite a source, it does not guess: if the answer is not in your documents, it says so and the question goes into a missing-information report. Users can check every answer against the original.
No. The assistant only answers from documents the person asking is authorised to see. HR, finance or management documents stay closed to users without permission, and their content does not surface in answers either. One assistant can therefore serve several departments while your existing document access rules still apply.
It does not have to be. With open-source language models, the assistant can run entirely on your own servers, so neither your documents nor the questions are sent to an outside AI service. This suits organisations, or departments working with contracts, personnel files or regulations, whose data must not leave the premises. The right setup is agreed during the needs analysis.
Procedures, technical manuals, contracts and training material are turned into a searchable knowledge base. PDF, Word, Excel and scanned documents can all be processed. The most frequent topics and the questions the assistant could not answer are reported, which shows which procedures are missing or out of date.
Through a web interface, your intranet, WhatsApp or your existing help desk, so staff do not have to learn a new application. If the assistant needs to serve customers, the same approach can be built as a chatbot for your website and WhatsApp.
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