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Enterprise RAG Chatbot

An accurate chatbot, grounded in your own knowledge

Chatonn is a RAG chatbot that retrieves answers from your knowledge base before responding - so it's accurate, up-to-date, and shows the source for every answer. No more hallucinations.

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Generic chatbots fail. RAG chatbots don't. your own knowledge

Ordinary LLM chatbots guess from training data. A RAG chatbot answers from the content you control.

Rule-based chatbots break the moment questions get creative
Raw LLMs hallucinate answers your customers can't trust
Outdated answers erode confidence in your brand
Customers can't verify where an answer came from
Every new feature forces you to rebuild your chatbot
A bad answer becomes a support ticket - or worse, a churned customer

Built for grounding, accuracy, and control

The retrieval layer that makes AI answer from what you actually know.

Your content, indexed

Upload documents or crawl your website. Chatonn chunks and indexes everything into a lightning-fast RAG store.

Citations on every answer

Every response links back to its source, so customers and agents can verify the answer instantly.

Choose any LLM

Power retrieval with OpenAI, Claude, Gemini, Groq, or self-hosted Ollama - whichever fits your quality and cost targets.

Governed, not guesswork

Answers come only from your approved content, supporting the security and compliance needs of enterprises.

Deploy your RAG chatbot in minutes

1
Add your knowledge base - upload PDFs, docs, and FAQs, or crawl your website and help center.
2
Connect an AI provider - pick OpenAI, Gemini, Claude, Groq, or Ollama, or bring your own API keys.
3
Embed the widget - drop in one script and your RAG chatbot answers visitors with cited, accurate responses.

Questions, answered

What is a RAG chatbot?

A RAG (Retrieval-Augmented Generation) chatbot answers questions by retrieving relevant chunks from your own knowledge base before generating an answer. That means responses are grounded in your content - accurate, up-to-date, and backed by citations - instead of relying on the model's general training data.

How is a RAG chatbot different from a regular chatbot?

A regular chatbot is rule-based or trained on generic data and can hallucinate. A RAG chatbot pulls from your actual documents, so it answers only from what you know to be true, and it shows the source for every answer.

What content can I train it on?

PDFs, Word docs, TXT files, FAQ pages, help-center exports, and your whole website or knowledge base. Chatonn chunks and indexes it automatically.

Is a RAG chatbot right for enterprises?

Yes. Because answers come from your governed content, RAG supports security and compliance needs that raw LLM chatbots can't. Chatonn adds multi-tenant isolation, RBAC, and audit logs for enterprises.

Can I use my own AI API keys?

Absolutely. Bring your own OpenAI, Anthropic, Google, or Groq keys, or use AI-managed responses - and route different conversation types to different models to control cost and quality.

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Deploy a RAG chatbot your customers trust

Connect your knowledge base, choose your AI models, and start deflecting tickets from day one.

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