CitySwift, Driving Modern Bus Networks Forward With AI & ML

LinkedIn Honour

It is becoming more common for urban bus networks to employ AI technology to improve planning and workflows. For one, it greatly improves decision-making capacity which invariably leads to making routes more efficient.

CitySwift, a Galway, Ireland-based startup whose data-driven decision-making AI platform solves the problems these said bus networks come up against. In 2021, the company was named in LinkedIn’s first-ever top ten list of most sought-after startups to work for in Ireland. The list highlighted emerging businesses that showed resilience during the Covid pandemic, with impressive growth and an ability to hire top talent.

Founded in 2016 by Brian O’Rourke and Alan Farrelly, CitySwift’s AI and machine learning (ML) tools can accurately predict journey times and passenger demand, creating optimized timetables that take into account traffic, events and hundreds of other external factors, ensuring on-time performance and increased passenger satisfaction.


Described by the tech publication siliconrepublic as one of the companies shaking up Ireland’s data science scene, the startup was selected in 2018 to join the Intelligent Mobility UK Accelerator Programme and Bank of Ireland’s Innovation Lab in New York City, while appearing in the Sunday Business Post’s prestigious ‘100 Hot Startups’ list a year later.

All these accolades have been earned, especially as CitySwift’s cloud-native, specialist bus data engine for modern bus networks is based on three products:

• SwiftMetrics: delivers bus network analysis at scale

• SwiftSchedule: rapidly generates optimized bus timetables

• SwiftConnect: enables the sharing of accurate bus capacity predictions on a stop-by-stop basis, helping passengers make the right journey choices

So how does the platform benefit urban bus networks exactly?

The platform is great for schedule planners, network operators and local authorities by vastly improving the efficiency of the customer’s network and ensuring every bus is where its customers expect it to be.

“Operational information is combined with a vast array of big data sources to develop rich datasets that are unique to each bus network and location. Machine learning models are trained on this data to deliver highly accurate predictions.”

 — CitySwift

With over 40 years of experience across the bus industry and a unique understanding of its operational challenges, the CitySwift founders and their dedicated team have deep public transportation domain knowledge, and are — in their own words — “ideally positioned to transform the way buses are scheduled.”

CitySwift’s CEO and first of two Co-Founders is Brian O’Rourke, a tech-savvy entrepreneur and former CitiBank analyst with a range of experience. Interested in computer programs from a young age, O’Rourke’s studies have included software engineering, business strategy and finance. At CitiBank, he led big data and complex optimization projects, specifically for the mobility sector.

O’Rourke obtained a BA in Entrepreneurship, Business Strategy, Finance and Accounting from Dublin City University.

His CitySwift founding partner is Alan Farrelly, the startup’s COO. Born into the bus industry, Farrelly’s family has operated a large fleet in Ireland since the 1980s. He has worked in every role within the industry — from driving and customer service to scheduling and operations. Farrelly brings this in-depth knowledge and experience to CitySwift to help solve the industry’s challenges.

He received a BA in Business from the National College of Ireland.

Since its founding in 2016, CitySwift has raised a total of $2.2 million in funding over two rounds. Institutionally backed, its investors include Ryanair co-founder Declan Ryan’s Irelandia Investments, ACT Venture Capital and former CarTrawler Chief Executive Mike McGearty.

With cities expanding at a steady pace, the demand for such data engine solutions as CitySwift’s to improve modern bus networks is much needed. This startup definitely has a great future ahead.