Axis 02 · Software engineering
Document AI (RAG)
Assistants that answer from your own documents, with automatic extraction and classification.
The challenge
The information exists, but it is scattered across documents, archives and shared folders: finding the right answer takes time and depends on a few people.
We build assistants that answer your teams' questions from your own documents, citing the passages they rely on. The RAG technique combines semantic search with a language model, so answers are grounded in your sources rather than general knowledge. NEXTBIT prepares and indexes your documents, respects access rights and can deploy the whole system on your servers, so your data never leaves your premises. We also handle automatic extraction and classification of documents.
What we do
- Document preparation: scanning, OCR, chunking and metadata
- Semantic indexing in a vector database such as Qdrant
- An assistant that answers with its sources, in Arabic, French and English
- Access rights respected: each user only queries authorised documents
- Automatic information extraction and classification of incoming documents
Our approach
- 01
Assessment
Choice of use cases, inventory of documents, their quality and confidentiality constraints.
- 02
Design
Architecture, choice of model and hosting, reference questions for evaluation.
- 03
Pilot
Assistant opened to a group of users on a real document set, evaluated on the reference questions.
- 04
Deployment and handover
Extension of the document set, monitoring of answer quality, documentation and team training.
What you gain
- Verifiable answers, with the source cited
- Your documents can stay on your own infrastructure
- Organisational knowledge available to every team
- Less time spent searching and filing
Frequently asked questions
Can the assistant make up answers?
The risk exists with any language model. We reduce it by requiring the assistant to rely on retrieved passages, cite its sources and say it does not know when the information is missing. Quality is measured on reference questions before and after deployment.
Are our documents sent to a foreign service?
Not necessarily. We can deploy the language model and the document base on your own servers, with no connection to an outside service. The hosting choice is made with you during design, based on the sensitivity of the documents and the hardware available.
What kinds of documents can the assistant use?
Office documents, PDFs, including scanned ones thanks to OCR, internal web pages and exports from your applications. Documents in Arabic, French and English are supported. The assessment checks the quality of the sources before work begins.
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