AI with your own documents: planning a knowledge assistant
Does your team regularly search manuals, project documents or internal instructions for answers? A knowledge assistant can bring relevant information together. What matters is which documents it may search, how current they are and whether its answers can be checked. Here is how to prepare a manageable pilot project.
1. Define the questions and documents
Start with a specific task, such as answering questions about an approved product manual. Collect common questions and the documents containing the answers. Check versions, ownership and readability: a scanned PDF may need text recognition, while tables and images require processing appropriate to the task. A large collection of files alone does not make a useful knowledge base.
2. Use relevant passages as context
Retrieval-Augmented Generation, or RAG, combines retrieval of relevant passages with generating an answer. For your documents, this means preparing the content, finding relevant passages and providing them to AI as context. This does not require training a separate language model on all your documents. Source references help with checking but do not guarantee a correct or complete answer.
3. Define access and updates
Define which users may see which sources. Retrieval and answers must respect these boundaries; a summary must not expose confidential content to other users. Also agree how changes and deletions are reflected in the search index and who corrects outdated information. Which data an external provider receives depends on the chosen environment and needs to be clarified beforehand.
4. Test with questions you can verify
Create a test set with expected answers and permitted sources. Include questions without a supported answer, conflicting versions and restricted access. Check separately whether retrieval finds the right passages and whether the answer represents them accurately. When evidence is missing, the assistant should ask for clarification or refer the question to a responsible person. Then compare search time and correction effort with your existing workflow.
These details help with planning
- Which questions should the assistant answer, and for whom?
- Where are the documents stored, and in which formats?
- Who may use which sources, and who keeps them up to date?
- Which answers and sources will provide a reference for the pilot?
Technical background on the RAG approach: Lewis et al.: Retrieval-Augmented Generation (2020, English).
Discuss your specific task
Tell us which questions the assistant should answer, what types of documents you have and who will use it. Please do not send confidential documents at this stage.