Choose sources and questions
We review representative documents, users and the questions the assistant should handle.
6G Web Studio · India
A retrieval-augmented generation assistant can search approved documents and draft answers with supporting references. We begin with your real questions, source material and access requirements.
Clear scope · Practical technology · Human support
The goal
A RAG system retrieves relevant sections from selected knowledge sources before generating a response. We plan ingestion, permissions, citations, evaluation questions and human fallback together; the system should be able to say when its sources do not support an answer.
Good fit when
We’ll check the project goal, existing tools and any outside dependencies before confirming the scope.
A clear process
The exact sequence depends on the work, but the decision points stay visible.
We review representative documents, users and the questions the assistant should handle.
We agree on access rules, citations, test cases, limitations and human escalation.
We test responses against your sample questions and adjust scope based on the results.
Common questions
No. Retrieval and citations can make answers easier to inspect, but they do not guarantee correctness. Testing, source quality and a clear human fallback remain important.
That depends on the chosen hosting and model setup, source permissions and data requirements. These details must be agreed before any documents are connected.
A small set of representative documents, common questions, intended users and any rules about what the assistant must not answer are a useful start.
See all frequently asked questions ↗
Have a project in mind?
Share your goal and what you already have. We’ll reply with questions and a clear next step.