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Illustrative example, not a specific client.

Illustrative example — this shows how a job like this typically runs, not a specific client engagement. Figures are representative, not measured outcomes.

Building a Shared E-Mobility Platform Around a Pricing Model That Had to Hold Up

How a solo founder's 40-rule pricing spreadsheet became a booking platform that charges the right amount every time, in every council zone.

Client
A solo founder in shared electric mobility
Sustainable Micromobility (E-Bikes & E-Scooters)
Location
Adelaide, SA
Pre-launch venture · solo founder
Time taken
5 weeks
Fixed timeline
Price
$4,350 AUD (fixed price)
Agreed before we started
What a job like this typically changes
40+
Pricing rules automated
Every rate, surcharge and discount recalculated live on each ride
3
Council zones at launch
Each with its own enforced no-go areas and speed caps
5 Weeks
Time to a working platform
From pricing spreadsheet to a bookable, paying platform
100%
Pricing accuracy
Tested against every rule combination before launch

Where they started

The situation

Local councils were willing to grant an operating permit, but only if the platform itself could enforce their rules — no-go zones, speed caps in shared paths, mandatory parking bays — without relying on riders to behave. On top of that, the founder's pricing model needed to combine time, distance, zone surcharges and membership discounts correctly on every single ride, with no room for a pricing bug to quietly undercharge or overcharge a customer.

The problem

Two agencies had quoted for 'an app', without seeming to register that the pricing and compliance logic was the actual product — the app around it was comparatively simple. Get the rules engine wrong and the business either loses money on every ride or loses its council permit.

What the first version had to get right

From the first read-through
Pricing lived in a spreadsheet no developer could read

40-plus conditional rules across vehicle type, time of day, zone and membership tier, worked out by the founder but never written down as logic.

A different rulebook per council

Each council had its own no-go zones, speed caps and parking rules, and reserved the right to change them with little notice.

Compliance meant proof, not just following the rules

Councils and the insurer both wanted ride and incident data retained and retrievable, not just a promise that the rules were being followed.

The business model itself was sound

The founder had done the hard thinking on pricing and unit economics — it needed software that wouldn't break under real bookings, not a rethink.

How the five weeks ran

Done in 5 weeks
Week 1

Turning the spreadsheet into a rules engine

Rebuilt the 40-plus pricing rules as data the app reads and recalculates from, live, instead of logic buried in code — so a rule can change without touching a line of code.

Week 2

Geofencing each council's rules

Built zone maps for each council area with its own speed caps, no-go areas and approved parking bays, checked automatically against the vehicle's live location.

Weeks 3–4

Booking, unlocking and payment

Built the ride flow — unlock, live pricing as the ride runs, in-app payment on completion — plus the member tiers and discounts from the original pricing model.

Week 5

Compliance logging and launch

Added ride and incident logging that councils and the insurer could be handed on request, tested the pricing engine against every rule combination, and launched in three council zones.

What was handed over

  • A pricing engine driven by rules data, not hardcoded logic
  • Geofencing enforcing each council's no-go zones, speed caps and parking rules
  • A full booking flow — unlock, live pricing, in-app payment
  • Ride and incident logging ready to hand to a council or insurer on request

What we built it with

We pick tools with low ongoing licence costs, solid privacy, and no lock-in — so you can take the work elsewhere if you ever want to.

React RouterMapboxStripeSupabase / PostgresCloudflarePostGIS

Sound like your situation?

Thirty minutes on a call is usually enough for us to work out where you're stuck, say whether we're the right people, and give you a firm price — before you commit to anything.