What makes software “mission-critical” in rail freight is changing. In an interview with RailFreight.com, Willem Jan Groenewoud, CEO of Ab Ovo, drew a sharp line between two worlds: the physical operation of trains and the administrative backbone that supports it.
The first depends on systems that simply cannot fail, where reliability, performance and cyber security dominate. The second, which includes contracting, ordering, production and invoicing, must minimise headcount through usability and functional coverage, but it can tolerate short outages without stopping trains.
On the operational side, Groenewoud underlined that reality rarely matches the plan. Planning is less a static timetable and more “continuous re-planning” across multiple constrained resources: paths, locomotives, wagons, driver duties and repositioning. A disruption on one axis quickly cascades across the rest. Back-office systems face different pressures. Here the litmus test is throughput with a lean team. Feature completeness and ease of use matter most, while a brief outage is inconvenient rather than catastrophic.
Single-wagon load: the toughest digital puzzle
Not all freight is equal from a software perspective. Block trains on simple A–B lanes are well served by many vendors. The difficulty rises sharply with single wagonload (SWL). Few tools tackle this well, Groenewoud noted, describing it as a genuinely complex multi-resource puzzle. The business challenge compounds the technical one: SWL flows are often less profitable, yet shippers expect providers to handle both block and SWL traffic. Operators that cherry-pick only the straightforward work risk losing the entire account.
Why non-functionals now outrank features
Compared with 20 years ago, Groenewoud argued that non-functional requirements — reliability, performance, scalability and especially cyber security — are now “more dominant than the functional requirements”. Generative coding assistants can spin up basic business applications quickly, but turning them into mission-critical systems remains hard because the craft lies in meeting those non-functionals at scale. “A generative ‘programmer on your shoulder’ can build features. It cannot, by itself, deliver the non-functional part,” he said.
AI’s role: three stages of impact
Groenewoud sees AI reshaping rail freight in three stages:
- Automation of repetitive tasks (one to two years): call centres, bookkeeping and routine analytics see large efficiency gains.
- Operational augmentation: planning and back-office processes benefit, but impact is incremental and business-case driven.
- Screenless and proactive systems: assistants monitor user behaviour, answer questions before they’re asked and assemble task-specific interfaces on the fly, integrating multiple applications behind the scenes.
Ab Ovo is already experimenting with voice-to-process tooling that converts spoken descriptions of workflows into business process models and starter applications. The company is working to embed safeguards for security, scalability and performance from the outset, and to align outputs with “green software” principles.
Energy, data centres and ‘green software’
As AI scales, energy use in data centres will grow. Policymakers are likely to constrain capacity in some locations, making software efficiency a strategic concern. Groenewoud advocates for “green software principles” and notes that language choice at runtime matters: carefully engineered low-level implementations can reduce consumption in production environments. “You’d better make sure mission-critical applications are extremely efficient for using less space in a data centre,” he said.
People, knowledge and the adoption curve
Despite the hype, AI will not replace locomotives, wagons or cargo. Value will accrue around the surrounding processes, where the business case remains decisive. A near-term priority is knowledge retention as experienced staff retire. Here AI can act as a persistent memory layer for procedures, constraints and best practice, shortening analysis cycles for new routes or customers and reducing reliance on large external consulting teams.
Bottom line
For rail freight operators, the software brief is crystallising. Keep trains moving through robust, cyber-secure platforms engineered for reliability and performance. Use AI to compress cycle times, predict needs and simplify interfaces — but don’t mistake fast feature generation for mission-critical resilience. And build with energy efficiency in mind, because scarcity in the data centre could soon be a competitive factor.