I built an conversational agent with RAG and Vector Search

Show HN: I built an conversational agent with RAG and Vector Search

Based, I built an conversational agent with RAG and Vector Search works in show hn launch.

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I’ve been building an embeddable AI agent that turns any website into an interactive, context-aware experience.Unlike typical FAQ bots or generic chat assistants, this one doesn’t just read your PDFs or docs, it also learns from how visitors interact with your site and adapts its responses, recommendations, or offers accordingly.Technically: • Runs fully client-side (no external API calls or backend dependencies) • Uses RAG pipelines to reference your own PDFs, documentation, or content base • Employs local embeddings to personalize context and answers per visitor session • Supports custom styling and can be embedded anywhere on the pageEarly results (from SaaS testers): • +25–30% increase i

As a business in show hn launch, I built an conversational agent with RAG and Vector Search is listed here with the public details available about it.

Its current recorded stage is Show HN launch.

Website: orchis.app