Real-world scenarios that show how our automation works — and the kind of results it's designed to deliver.
A note on these examples: The scenarios below are illustrative — they show exactly what we build for each situation and the outcomes these systems are designed to produce, based on how the underlying automation works. The figures are realistic targets, not results from named past clients.
A two-truck plumbing company is on the tools all day, so calls go to voicemail — and most callers don't leave one, they just call the next plumber. Evenings and weekends are worse. Every missed call is a job worth hundreds of dollars walking out the door, and hiring a full-time receptionist at $3,750+/month doesn't pencil out.
An AI phone agent that answers every call — including after hours and when the line is busy. It greets callers in the company's name, figures out what they need, books the job into the calendar, and captures the address and problem. The owner gets an instant text summary of every call, with genuine emergencies flagged and routed straight to their phone. Callers can ask to speak to a person at any time. Each booked call automatically kicks off a confirmation, a reminder before the visit, and a review request after.
An HVAC company completes 15–20 jobs a week but only picks up 1–2 Google reviews a month. Technicians are too busy to ask, and the office keeps forgetting to send follow-ups — so a middling star rating drags them below competitors sitting at 4.5+.
An automated review request system triggered by their job management software. When a technician marks a job complete, the customer gets a branded email 2 hours later with a direct link to the company's Google review page. If no review is left after 3 days, a gentle follow-up goes out. Negative feedback (detected via a pre-screen question) gets routed to the manager instead of Google.
A clinic loses meaningful revenue every month to no-shows. The front desk manually calls patients to remind them, burning a couple of hours a day on the phone — time they don't have.
An automated reminder system connected to their booking software. Patients get a confirmation email when they book, a reminder 24 hours before, and a final reminder 1 hour before their appointment. No-shows automatically receive a rebooking email the next morning with a link to reschedule. The front desk is freed up entirely.
A contractor gets 30+ quote requests a month from their website and Facebook ads but closes only a fraction. Leads sit in an inbox for days before anyone replies — and by then most have already hired someone else.
An instant lead response system. The moment a quote request comes in, the customer gets a personalized auto-reply within 30 seconds. The lead is logged in a database, categorized by project type (kitchen, bathroom, basement), and the right estimator gets an email with all the details. If no quote is sent within 48 hours, the system flags it and reminds the estimator. After a quote is sent, automated follow-ups go out at 3, 7, and 14 days.
A supplier spends 5+ hours a week creating invoices in Word, emailing them out, and chasing payments with awkward phone calls. On average they wait weeks to get paid — and some invoices are simply forgotten.
An automated invoicing pipeline. When an order is marked fulfilled, the system auto-generates a professional branded invoice and emails it to the customer. If unpaid after 7 days, a polite reminder goes out. At 14 days, a firmer follow-up. At 30 days, a final notice. When payment is received via Stripe, the system marks it paid and sends a receipt automatically.
A brokerage's agents want to stay on top of market news — zoning changes, interest rate updates, competitor listings, local development — but nobody has time to read the news every morning. They miss opportunities because they don't know what's happening in their own market.
A custom daily news briefing engine. Every morning at 7am, the system scans hundreds of news sources for articles relevant to the brokerage's market — filtered by location, competitors, and industry keywords using rules we set up with the team. The engine ranks each article by relevance, selects the 5 most important, and writes a one-sentence "why it matters" for each. The briefing lands in every agent's inbox before their first coffee.