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9 min read

Chatbot Trained on Your Data: Accurate, On‑Brand Answers

Ground every response in your content with retrieval‑augmented generation (RAG) backed by vector search.

Why training on your data matters

  • Answers reflect your exact product and policies.
  • Consistency with brand tone and documentation.
  • Lower risk of hallucinations with source grounding.

How ChatDock implements RAG

  1. Read: your website’s pages, your PDFs, your YouTube videos and the answers you write yourself.
  2. Chunk & embed: generate vector embeddings per chunk.
  3. Retrieve: match relevant chunks per query.
  4. Generate: craft concise answers with sources.

Keeping answers trustworthy

  • It answers only from what you added, and says so when that doesn’t cover a question.
  • Each answer can link to the page, file or video moment it came from.
  • Re‑read pages when they change, so answers stay current.