- Answers cite their source
- Arabic and English
Your team already knows the answer is in a document somewhere. The problem is finding it: the latest version of the policy, the clause in last year's contract, the procedure for the case that comes up twice a year. Public chatbots cannot see those documents, and pasting them in raises a data question you should not have to answer.
We build private knowledge bases using retrieval-augmented generation, usually called RAG. The assistant searches your own documents, answers in Arabic or English, cites the passage it relied on, and only shows each person what they are already allowed to open.
What is included
- Document ingestion. Policies, manuals, contracts and reports loaded from your drives, intranet or document system, including scanned PDFs.
- Answers with sources. Every answer cites the document and passage behind it, so staff can check rather than trust.
- Permission-aware search. People only get answers from documents they already have the right to open.
- Arabic and English. Questions in either language, answers in either language, across documents written in both.
- Private deployment. Runs in your environment or a UAE region you choose, so documents do not leave your control.
- Quality checks. A test set of real questions used to measure answer quality before launch and after every change.
How the engagement runs
- Scope. The quotation on this site captures your document types, volume, users and hosting needs.
- Pilot collection. One department's documents loaded and tested against its real questions.
- Measure. Answer accuracy and source quality checked with the people who will use it.
- Roll out. More collections and teams added, with permissions mapped for each.
Questions
What is a RAG chatbot?
RAG means retrieval-augmented generation. Instead of answering from general training data, the chatbot first searches your own documents for the relevant passages and then writes an answer from them, citing where each part came from. That is what makes it accurate on your company's information.
Is a private AI knowledge base like ChatGPT for business?
It works in a similar way for the user, but it answers from your own documents, respects your access permissions and can run inside your environment. Your documents are not sent to train a public model.
Does it work with Arabic documents?
Yes. It searches and answers across Arabic and English documents, and a question asked in one language can be answered from a document written in the other.
How much does an AI knowledge base cost?
It depends on the volume and type of documents, the number of users and where it is hosted. Starting with one department's documents keeps the first phase small. The quotation on this site gives you a scoped estimate in AED.
Go deeper: Enterprise knowledge systems on lenouar.ae