What if you could take a real operational problem from the rail freight industry and turn it into a working AI prototype in an afternoon? 

That’s exactly what happened at railXchange 2026 in Frankfurt. Next to the usual panels and presentations, Rail-Flow and Menlo79 ran a live AI hackathon under the theme rAIl Innovation Now. Customers and industry professionals didn’t come to watch a demo, they came to build one. 

Eight teams tackled four challenges pulled straight from the operational reality of rail freight: 

• AI-powered infrastructure document management: categorizing emails about route changes and visualizing them on an interactive map 

• Intelligent inbox automation: classifying incoming emails, routing tasks, and generating automated replies for standard message types 

• A marketplace for wagon storage: connecting track owners with operators needing temporary siding space, think “Airbnb for sidings” 

• A shift exchange portal for rail staff: replacing ad-hoc message chains with a structured, automated system for drivers, dispatchers, and yard teams 

Two teams competed on each challenge independently, making it possible to compare not just the solutions, but the thinking behind them. Every team worked with the same two tools Rail-Flow uses in daily work: Cursor for development and Figma Make for design mockups. 

The results spoke for themselves

By the end of 150 minutes, all eight teams had something to show, such as working prototypes with real interfaces, functional logic and actual tools. 

Some examples of those were the infrastructure monitoring app, that drew an immediate reaction from an attendee who wanted it integrated into her company’s existing system on the spot. The email automation prototypes showed that intelligent triage of rail operations inboxes is not a distant possibility, it can be set up in an afternoon. The wagon storage marketplace gave shape to a commercial model the industry has been circling for a while. And the shift exchange platform replaced a genuinely painful coordination problem with something clean and automatable. 

What it actually proved

The format was designed to test a hypothesis: can rail freight domain experts, not AI specialists, produce functional prototypes in a constrained time window, using tools available today? The answer was clearly yes.  

One jury member put it plainly: “We have demonstrated that we can get really good results in a very short amount of time. And it’s repeatable.” 

Another drew a contrast with how the industry has historically approached software investment: “I’ve seen so much money burned over the decades because of unclear requirements. What we built here is actually working, that’s not something old-school prototyping ever delivered.” 

Many of the participants came in with limited prior AI experience. They left having built something together and, more importantly, with a concrete sense of what’s now possible in their own organizations. 

The bigger point

Speed matters, but it’s not the whole story. What the hackathon demonstrated is that the gap between identifying a problem and having a working solution in front of you has collapsed, when you have the right tools and the right people around you. 

Rail freight has always had complex operational challenges from inbox overload to fragmented infrastructure data and manual shift coordination. None of that is new. What is new is the speed at which those challenges can become working solutions. Not a concept document or a roadmap, but a clickable, testable prototype built in an afternoon, ready to put in front of the people who actually do the work. 

That’s the opportunity Rail-Flow is building toward. 

Interested in exploring what AI could look like for your rail operations?  Get in touch with Rail-Flow’s Transformation AI manager  Melanie Maszke (m.maszke@rail-flow.com)