Trained on the brand's own knowledge, it answers across every channel — and hands off cleanly when a human is needed.
A direct-to-consumer brand fielding the same product, shipping, and returns questions across email, web chat, and WhatsApp.
Support volume spiked with every promotion. Response times slipped, the small team burned out on repetitive questions, and answers varied depending on who replied.
Trained on the brand's product docs, policies, and past tickets, it answers across every channel — and escalates cleanly when a human is needed.
A customer asks on any channel; the agent answers from the brand's actual knowledge base, not generic guesses.
For order-specific questions it looks up the order and responds with real status.
When a question is sensitive, ambiguous, or outside policy, it escalates to a human with the full conversation attached.
Every resolved conversation feeds back to improve the knowledge base.
The pattern: a workflow backbone, a reasoning layer, a system of record, and a channel. The system handles volume and routine; people handle judgment and exceptions. That's what makes it an automation the business can trust — not AI running unsupervised.