AI Acceptable Use Policy: What to Include, Who Signs It Off and How to Make It Stick
What belongs in an AI acceptable use policy and who signs it off? Use our section outline, use-case matrix and seven-step plan to draft yours this week.
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Enterprise LLM Assistant
What Is an Enterprise LLM Assistant?
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. The approach is known as RAG (Retrieval-Augmented Generation): the assistant first finds the passage that contains the answer, writes its reply based only on that passage, and shows the source. Staff can check any answer against the original, and nothing that isn't in your documents gets made up.
What the Assistant Does
A Knowledge Base From Your Files
Procedures, manuals, contracts and training material become a searchable knowledge base. PDF, Word, Excel and scanned paperwork are all processed.
Answers With Citations
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.
Permission-Aware Access
The assistant answers only from documents the person asking is entitled to see, so HR, finance and board material stays with the right people.
In the Channels Your Teams Use
Available through a web interface, your intranet, WhatsApp or your existing helpdesk, so nobody has to learn yet another tool.
Runs on Your Own Servers
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.
Question Reports & Gap Finding
Top topics and unanswered questions are reported, showing which procedures are missing or out of date.
Who Uses It, and for What
- HR policy, leave and employment questions
- Field service and troubleshooting guides
- Quality procedures and ISO documentation
- Product and price-list answers for sales teams
- Finding clauses in contracts and regulations
- Onboarding new starters
- Dealer and customer support lines
- Regulatory guidance in public institutions
If the assistant will face your customers, see NLP & chatbots. If you simply want to manage your files and ask built-in AI questions about them, with no installation, SmartFiles from the Smart360 family is worth a look.
How We Set It Up
01
Scope & Document Inventory
We agree which documents feed the assistant, who will use it and which types of question it must handle.
02
Knowledge Base Build
Documents are split into passages and indexed in a vector database; scanned records go through OCR and access rules are defined.
03
Testing With Real Questions
We test with questions your people actually ask, review wrong or incomplete answers and tune retrieval and response settings.
04
Launch & Monitoring
The assistant goes live on its channels and usage is tracked. New documents are added to the knowledge base automatically.
Stopping Made-Up Answers Is a Design Choice
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.
Questions we hear most often
Frequently Asked Questions
What is an enterprise LLM assistant?
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.
What is RAG, and how does it stop the assistant making things up?
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.
Will the assistant show information a user is not allowed to see?
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.
Is our data sent to external AI services?
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.
Which document types can the assistant use?
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.
Where do staff use the assistant?
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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