Case study · Transit · Tri-State Transit Authority, WV
NS
“
A no-show isn’t just wasted fuel and driver time — it’s a seat someone else needed.”
Nick Smith, Assistant Manager, Tri-State Transportation Authority, WV
Agency snapshot
Tri-State Transit Authority (TTA), West Virginia.
Paratransit dial-a-ride, 40,000 trips/year.
Nick Smith, Assistant Manager.
The Problem
TTA runs its paratransit dial-a-ride service on a software without automated callout system. No-shows were invisible until they’d already happened: wasted fuel, wasted driver time, and a seat someone else needed. Nick was determined to find a solution to those pesky no-shows.
trips a year
no-shows last year
6.9%
no-show rate
$22.40
lost per trip
"At $22.40 per trip, this all adds up. Every penny counts.”
“The frustrating part about it is we didn’t really have any way to see no-shows coming. We were just reactive when they did happen.”
Two ways out before AI: a vendor contract, or staying reactive.
Nick asked the data for a solution, instead.
What he did · about six calls A NIGHT
1
He started with his own data
Nick fed a year of trip data into one Claude conversation.
2
He let the data overturn his assumptions
The riders he expected to be reliable weren’t. The trips he expected to be shaky held. The data challenged all of his assumptions.
3
He had Claude build a no-show scoring tool
An Excel workbook that scores every rider from zero to one hundred and generates a nightly priority call list.
4
He built a process around the tool
Dispatch works the list every night — about six calls per shift. On bad-weather days, they call deeper into the list.
5
The tool went above and beyond
Along the way they fixed bad phone numbers and rider data thanks to the new process.
Before AI Adoption:
2,800 no-shows
After AI Adoption:
$15,000+
projected year 1 savings
— Nick Smith, Assistant Manager, Tri-State Transit Authority
What this means for you
“I'm not a programmer, but just sitting with AI made the solution so clear. So clear!”
— Nick Smith (recently promoted thanks to his problem solving)
You might not need that expensive vendor contract to close your own operating gap.
What could happen if you just asked AI for your ideal solution?
More stories
Transit
Federal Reporting: Automating NTD
The federal report every transit agency dreads, done in 25 minutes.
Case study
Read the story
⟶
Transit
Resource Scheduling: Paddles
Turning thirty years of handwritten scheduling into a permanent system.
Case study
Read the story
⟶
Government
Regional Strategy: Streamlining CEDS
A five-county strategy that takes months, drafted live in one afternoon.
Case study
Read the story
⟶