The AI pipeline
When a customer sends a message, Chatonio's AI pipeline processes it through several steps:
- Context building — the system prompt, conversation history, relevant FAQ entries, and knowledge base articles are assembled
- AI response — the configured AI model generates a response using this context
- Grounding check — before delivery, the drafted reply is automatically audited. Responses containing facts, IDs, amounts, or website URLs that aren't backed by a tool result, the customer's own messages, or your KB/FAQ are blocked and replaced with a safe fallback (and the conversation is escalated to a human). If the customer pasted a URL matching one of your configured integrations, the AI is forced to actually look it up via the tool instead of guessing
- Escalation check — a lightweight check determines if the conversation should be flagged for human review
- Delivery — the response is sent back through the originating channel
The grounding check is why the AI can't invent order details or links — if it can't back a claim up, the claim doesn't reach your customer.
Knowledge sources
The AI draws from two main knowledge sources to give accurate answers:
- FAQ entries — question/answer pairs matched by meaning (semantic search), so a customer's question matches even when it's phrased differently or asked in another language
- Knowledge base articles — longer-form content; the best-matching articles are found by meaning and injected as reference, with translations automatically used to match the conversation's language
Both FAQ and articles must have AI enabled turned on to be included in the AI's context.
Model configuration
Chatonio runs the AI models for you — there's nothing to install or connect. Each project can configure:
- Primary model — used for customer responses (higher quality)
- Utility model — used for summaries, escalation checks (lower cost)
Models are configured at the project level and can be overridden per channel.