01
You add sources
Upload PDFs, DOCX, TXT, CSV, TSV, JSON or HTML, paste FAQs and policies, or point the crawler at a URL. Every type is normalised into one clean, AI-friendly format.
Retrieval-augmented generation
A RAG chatbot that only
knows your business.
Generic chatbots improvise. A RAG chatbot retrieves your own documentation before it answers, so every reply is traceable to something you actually wrote. Softsasi Agent AI handles the chunking, embedding and retrieval for you — you just add the sources.
How retrieval works here
02
We chunk and embed
Each source is split into overlapping passages and embedded with text-embedding-3-small, then stored as vectors alongside canonical fields for exact lookups.
03
Retrieval on every question
A visitor question is embedded and matched against your vectors. Only the top passages are handed to the model — so the answer comes from your material, not the open internet.
04
Grounded answer, with an exit
The agent answers from the retrieved passages and cites what it used. When your knowledge doesn't cover it, it collects the visitor's details and escalates to a human instead of guessing.
Why teams pick RAG over a raw chatbot
- Fewer wrong answers
- The model is constrained to retrieved passages, so it can't invent a refund policy you never wrote.
- Updates land instantly
- Change a document and the next question uses it. No retraining, no fine-tuning bill.
- Same brain for chat and voice
- The text widget and the live voice call retrieve from the identical knowledge base.
- Structured intake
- Orders, complaints, tracking lookups and leads land in admin sheets you can filter and export.
Point it at your docs today
Trial starts at $1/mo — one agent, 100 conversations. Upload a document, publish the widget, and watch it answer from your own material.
Start free