DevraByte AI

Instead of asking a model to freely generate an action and hoping it's well-formed, every agent is given a fixed set of tools it can call — book an appointment, place an order, log a service request, or capture a lead. The model decides which tool fits the conversation; the tool itself defines exactly what gets written to the database.

A customer-facing agent handles bookings, orders, and enquiries over WhatsApp. A separate staff-facing agent — routed by matching the sender's phone number against your team — handles status checks and task updates instead, so a customer message and a staff message never get treated the same way.

Rather than guessing a conversation's intent up front and hoping the guess holds, each conversation is tagged with the outcome of whichever tool actually fired — booking, order, service request, lead, or general enquiry. That gives you an accurate breakdown of what your WhatsApp line is really being used for.

Common first-contact questions are cached so repeat questions don't re-run inference every time, and every AI call is gated behind your organization's plan.