RAG Chatbot for
Your Website
RAG (Retrieval-Augmented Generation) helps AI answer from your own content instead of memory. ChattyBox gives you a managed retrieval flow for websites, docs, CMS pages, and help centers.
What is RAG?
RAG combines a language model with retrieved source content. Before generating a response, the chatbot searches your published pages for passages that match the question.
Retrieve
When a visitor asks a question, ChattyBox searches indexed website, docs, help, and CMS content for relevant passages.
Augment
Those source passages are added as context so the model has something specific to answer from.
Generate
The model generates a concise answer and can include source links so visitors can verify the details.
How ChattyBox keeps retrieval practical
Searchable Content Index
Your website, docs, help center, and CMS pages are indexed so the chatbot can search the content you already publish.
Embeddings Model
Embeddings help match visitor questions to relevant source passages even when the wording is different.
Focused Retrieval
For each question, ChattyBox retrieves a small set of relevant passages instead of asking the model to answer from memory.
Context-Limited Prompting
The answer step is constrained to the retrieved context and configured to avoid unsupported claims.
Citation Links
Every response includes links to source pages, so users can verify the information.
Fallback Handling
When relevant content is missing, the bot can fall back instead of improvising an unsupported answer.
RAG without rebuilding your content stack
Connect your existing site content, test answer quality, and embed a source-cited chatbot when the responses look right.
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