How an Agent Would Actually Handle This
We don't have a product sandbox to hand you, so there's no live or interactive demo on this page. What's below instead is a narrated, step-by-step account of how an agent like ours would work through one specific, realistic interaction — the same decisions it would make, in order.
Not a Live Demo
Nothing on this page is running, clickable, or connected to a real system — it's a written walkthrough of the decisions an agent would make in a realistic situation, so you can judge the reasoning without needing us to spin up a sandbox. If you want to see something running against your own tools, that happens during a scoped build, not on a marketing page.
A Prospect Messages on WhatsApp at 9pm
A prospective customer sends a one-line WhatsApp message asking about pricing for a service, outside business hours.
The agent reads the message and the conversation history
It checks whether this number has messaged before and what, if anything, is already known — instead of opening with a question the prospect already answered last week.
It replies with what it can answer directly
General pricing information it's been approved to share, in the same tone the business actually uses on WhatsApp — not a copy-pasted email signature.
It asks the one or two questions that matter next
Just enough to tell whether this is a fit — job type and rough timeline, for instance — instead of a long qualifying script that reads like a form.
It decides: answer further, or hand off
If the prospect asks something outside what it's approved to say — a custom quote, a contract term — it says so plainly and flags the conversation for a person to pick up in the morning, with the full thread attached.
It logs the outcome
The conversation and any qualifying answers are written to the CRM the business already uses, so nothing is lost between the WhatsApp thread and the next day's follow-up.
Illustrative walkthrough, not a real conversation transcript or a live system. See AI WhatsApp Agents and AI Lead Qualification.
A Caller Wants to Reschedule an Appointment
A patient calls a clinic's main line during a busy morning to move an existing appointment.
The agent answers and confirms who's calling
It asks for enough to look up the existing appointment — name and date of birth, for instance — the same information a front-desk person would ask for.
It looks up the existing booking
Reads the current appointment from the scheduling system rather than asking the caller to repeat details already on file.
It offers real available slots
Checked live against the actual calendar, not a generic "we'll call you back" — and reads them out clearly over the phone.
It confirms the change and updates the record
Once the caller picks a slot, it moves the appointment in the scheduling system directly and confirms the new time back to the caller before hanging up.
It escalates anything outside a simple reschedule
A question about symptoms, billing, or anything clinical goes straight to a person — rescheduling is the boundary of what this agent decides on its own.
Illustrative walkthrough, not a real call recording or a live phone system. See AI Receptionist and AI Appointment Booking.
A Vendor Invoice Lands in a Shared Inbox
An email arrives in a shared operations inbox with a PDF invoice attached, mixed in among unrelated messages.
The agent classifies the message
It recognises this as an invoice rather than a general enquiry, based on the sender pattern and the attachment, and routes it differently from everything else in the inbox.
It extracts the structured details
Vendor name, invoice number, amount and due date, read out of the PDF rather than requiring a specific template.
It checks its own confidence
If the layout is unfamiliar or a field looks ambiguous, it does not guess — it flags the document for a human to confirm before anything is filed.
It files the confident cases directly
Clean, recognised invoices are entered into the accounting system automatically, with the source email linked for reference.
It leaves an audit trail either way
What it extracted, what it filed, and what it flagged are all visible afterward — not a black box someone has to trust blindly.
Illustrative walkthrough, not a real inbox or a live system. See Document Processing Agents and AI Email Agents.
Want to Walk Through Your Actual Scenario?
Bring the real interaction — the messages, the calls, the documents — and we'll tell you plainly how an agent would handle it, and where it should stop and hand off.