PricingCase StudiesAboutBlogFree Audit

Case Studies

Real results. Real businesses.

One of these is a live deployment with numbers pulled from the client’s own database. The rest are models, built from industry benchmarks, and we label them as such. You should be able to tell which is which at a glance.

The three below are models. Unlike the Beyond Limits study above, they are not drawn from a specific client’s data. They are built from industry benchmarks to illustrate the shape of outcome these systems produce, and the numbers in them are projections rather than measurements.

HVAC & PlumbingModel Case Study

How an HVAC contractor recovered $370K in missed revenue with AI voice agents

The Problem

A 22-person HVAC company was missing 40% of inbound calls during peak season. Their front desk staff couldn't keep up with the volume, and every missed call was a potential $800-$2,500 service job walking to a competitor. They estimated $500K+ in annual lost revenue from unanswered calls alone.

The Solution

We deployed two AI voice agents trained on their service catalog, pricing tiers, and scheduling system. The agents handle inbound calls 24/7, qualify leads based on job type and urgency, book appointments directly into their CRM, and route emergency calls to the on-call technician.

$370K
Revenue recovered annually
98%
Call answer rate (up from 60%)
24/7
Coverage without adding staff
2 weeks
From kickoff to live deployment
Med Spa & WellnessModel Case Study

How a med spa 3x'd their booking rate with automated lead nurturing

The Problem

A boutique med spa with 3 locations was generating 200+ leads per month from social ads but converting less than 8%. Their team was manually following up days after the initial inquiry, by which time most leads had booked with a competitor or lost interest.

The Solution

We built an automated lead nurturing pipeline: instant SMS and email follow-up within 60 seconds of form submission, a 7-touch nurture sequence over 14 days, an AI chatbot for answering treatment questions, and automated booking links pushed at optimal engagement windows.

3x
Booking rate (8% to 24%)
< 60s
Average lead response time
$18K
Additional monthly revenue
15 hrs
Staff time saved per week
Property ManagementModel Case Study

How a property management firm saved 40 hours per week with automated dispatch

The Problem

A property management company overseeing 340 units was drowning in tenant maintenance requests. Two full-time staff members spent their entire day fielding calls, logging tickets, and coordinating vendors. Response times averaged 18 hours, and tenant satisfaction was declining.

The Solution

We deployed an AI voice agent for inbound maintenance requests that categorizes issue type and urgency, an automated dispatch system that routes tickets to the right vendor based on availability and specialization, and a tenant communication workflow that sends status updates at every stage.

40 hrs
Saved per week on dispatch
2 hrs
Avg response time (from 18 hrs)
92%
Tenant satisfaction score
$4,200
Monthly labor cost savings

Want results like these for your business?

Every business is different. Get a free automation audit and we'll project specific outcomes for your industry, team size, and current workflow.