Can I vibe code Chatbase?
Train a support chatbot on your docs, embed it on your site.
This is RAG-as-a-service, and RAG is exactly what our Agentic AI course teaches you to build: chunk your docs, embed them, retrieve relevant passages, answer with citations. A personal version — your docs, an embed widget, honest 'I don't know' fallbacks — is a weekend build that our curriculum walks step by step. The kinda is for production support duty: evaluation, hallucination control, and handoff-to-human flows are where the $150/month stops looking silly.
Build a RAG chatbot for my documentation. Ingest: point it at my docs folder (markdown) or a sitemap; chunk (~500 tokens, overlap), embed with an embeddings API, store vectors in Postgres with pgvector. Chat API route: embed the question, retrieve top-6 chunks, answer with an LLM citing source titles/links, and refuse gracefully when retrieval confidence is low (show the threshold in config). Embeddable widget: a small script tag that renders a chat bubble on any site. Log every conversation to a transcripts table with a review page. This mirrors the RAG module in our Agentic AI course — comment each pipeline stage.
A RAG chatbot over your own docs with an embeddable widget: retrieval with citations, refusal on low confidence, and a transcript log you review.
- Managed evaluation and hallucination guardrails at scale
- Human-handoff, lead capture, and team inbox features
- Auto re-crawl and sync of changing documentation
- Multi-model routing tuned for support economics
Businesses want someone else accountable for the bot answering customers wrong — the ops and evals, not the RAG, justify the invoice.
A prompt is the first move, not the whole game. Course 01 teaches you to take a prompt like this one to a shipped, working app — reviewing, correcting, and steering the agent the whole way.
Start Course 01 →