Guy runs a mobile vehicle inspection service across Greater Sydney. The old booking system had him zigzagging across the city, spending 3+ hours just driving between jobs. We built an AI scheduling system that clusters appointments geographically and validates travel times in real-time.
40% Less Driving, Same Number of Jobs
Smart scheduling that actually works
Guy runs a mobile vehicle inspection service across Greater Sydney. Before this system, he was zigzagging across the city, spending 3+ hours just driving between jobs. Now the AI clusters appointments geographically and validates travel times in real-time.
The Result
The Problem: Random Booking Chaos
The old booking process was reactive. Customer calls, staff checks the calendar, guesses at a time. No consideration of where the technician will be before or after. The result? Days that looked like this:
Monday Before Optimization
The Problem We Solved
Before vs After
Manual booking with no travel consideration. Technician zigzagged across Sydney, 3+ hours driving between jobs.
AI validates travel times in real-time. Both legs must be under 35 mins or the slot is rejected. Geographic clustering automatic.
The Solution: AI That Thinks About Geography
We built a scheduling engine that checks every potential time slot against real travel times. Before accepting a booking, it calculates: How long to get there from the previous job? How long to get to the next job? Both must be under 35 minutes or the slot gets rejected.
Load Context
Pull all existing calendar events for the next 14 days, plus the customer's address and availability preferences.
Check Each Slot
For every potential time: skip weekends, skip full days (8+ jobs), skip conflicts, then calculate travel times via Google Maps API.
Validate or Fallback
If travel is under 35 mins both ways, book it. If no slot fits, find the closest existing job and schedule nearby for clustering.
How The System Works
Smart Scheduling Logic
- 1
Load calendar + customer preferences
- 2
Calculate travel FROM previous job
- 3
Calculate travel TO next job
- 4
Both under 35 mins? Accept slot
- 5
No match? Cluster near closest job
Scheduling Flow
Schedule Transformation
Daily Schedule
Random bookings, 3+ hours driving between jobs, zigzag routes
Geographic clusters, 10-15 min between jobs, regional routes
Schedule Transformation
Real Test: Natasha from Woronora
Woronora is isolated in the Sutherland Shire. Most of the week's jobs were in the northwest—over an hour away. The old system would have just picked the first available slot. Here's what the smart system did instead:
Customer Location
Woronora, NSW (Sutherland Shire)
The Challenge
- From Wahroonga (Tue): 1 hr 4 mins
- From North Ryde (Tue): 45 mins
System Decision
Found Beata at 10 AM Thursday in Gymea (also Sutherland Shire)
Travel Woronora → Gymea: 10 minutes ✓
Generated Response:
"Hi Natasha, we can schedule you in next at Thu 4th at 9:00 AM"
Real Test Case
Natasha from Woronora
1hr+ travel rejected
Found Sutherland cluster
10 min travel confirmed
System found geographic cluster: Woronora to Gymea
Thursday After Optimization
The Insight
The system doesn't just find available slots - it finds EFFICIENT slots. Every booking is validated against real travel times before it's offered.
— Smart Scheduling Logic
Why This Works
Business Impact
Results After Implementation
Fuel Savings
Weekly Fuel Savings
From optimized geographic clustering
API Costs Under Control
Tech Stack
The Bottom Line
43% less driving + 30% more capacity + instant responses = system pays for itself in week one
What's Next
Current System
- Single technician support
- Human confirms each booking
- Real-time travel calculation
- Geographic clustering
- Customer availability respect
Future Roadmap
- Multi-technician routing
- Fully automated booking
- Predictive clustering
- Route caching
- Customer area suggestions
The Bottom Line
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AI Smart Scheduling for Mobile Inspections
Pink Slips NSW Case Study
Reducing travel time and increasing jobs per day
AI scheduling clusters jobs geographically
Before vs After
Random booking order, wasted travel
Geographic clustering, optimized routes
How It Works
- 1
Customer selects availability
- 2
AI finds optimal time slots
- 3
Travel time calculated in real-time
- 4
Jobs clustered by area
For 100 bookings with smart caching
Tech Stack
- 1
Google Distance Matrix
- 2
PostgreSQL + Drizzle
- 3
React + TypeScript
- 4
Twilio SMS
This system pays for itself many times over. Less fuel, more jobs per day, happier customers.
— Jordan James
See It In Action
Book a Pink Slip inspection and experience the smart scheduling
Pink Slips NSW
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