Service 04 of 07
You said: “Customers ask the same questions and we answer them by hand.”
A chatbot that knows what it does not know
A chatbot that answers from your own documents and says so when it does not know.
Most chatbots on the market invent plausible nonsense. A retrieval-augmented system is different: it looks up your actual documents first, and only answers from what it finds.
When the answer is not in your material, it says so and offers to hand the question to a person. That single behaviour is the difference between a useful assistant and a liability.
This is for you if
Organisations with real documentation that customers or staff keep asking the same questions about.
This is not for you if
The knowledge lives only in people’s heads, or the answers change faster than you can update the documents.
Technologies involved
- Retrieval-augmented generation
- Vector search
- Large language model APIs
- Next.js
What is included
- A review of your existing documentation and where it is weakest
- Chunking and indexing designed around your content, not a default
- Citation of the source document for every answer
- An explicit refusal path when confidence is low
What you receive
- A working assistant embedded on your site or in your tools
- An index you can update as your documents change
- An analytics dashboard showing real questions asked
- A cost estimate before the bill arrives
Outcomes to expect
- The routine questions answered in seconds, at any hour
- Support volume down without making existing customers feel ignored
- A clear record of what people actually ask, which is free market research
Next step
Ready to talk about rag chatbot integration?
Describe the problem rather than the solution. We will tell you what rag chatbot integration would involve here, and whether a smaller first step would serve you better.
We reply within one business day.