AnAIvoiceagentthatanswerswiththecompany'sowninformation
A voice agent connected to an in-house knowledge base (RAG): it answers from the organisation's real documentation, not from generic data.
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How it works, step by step
This is the real system, told the way the customer experiences it.
Step 1 of 4
An employee asks out loud
As if they were calling a colleague who knows everything.
Step 2 of 4
It searches the company's documentation
It does not make things up: it queries the client's own knowledge base.
Step 3 of 4
It drafts the answer from that information
With the company's actual rule and the reference it comes from.
On the night shift on floor 2 you need a helmet, a hi-vis vest and S3 safety footwear.
You also have to check in with the shift supervisor before entering.
Source: Operations manual v4, p. 27
Step 4 of 4
And it answers out loud
No digging through a PDF, no waiting for someone to answer.
«Para planta 2 en turno de noche necesitas casco, chaleco y calzado S3, y fichar la entrada con el responsable de turno.»
Answered in 4 secondsThe problem
Where we started
An AI agent that makes things up or answers generically is useless: it has to answer with the company's specific information.
What we built
What we did
We built a voice agent with retrieval over an in-house knowledge base, hosted in the client's environment, that answers citing their documentation.
Benefits
What the business gains
- It answers with the company's real documentation, not generic text.
- The data stays inside the client's environment.
- Always available to resolve questions on the spot.
In-house
Knowledge base
From their info
Answers
In their environment
Data
Want this for your business?
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