OVRLAI: How Railroads Are Training Crews on Equipment That Hasn't Been Built Yet
February 18, 2026 • A5 Rail
Here's a scenario every Director of Training, Safety, and Operations at a mid-sized railroad has lived through.
A capital project wraps up. New infrastructure is commissioned. And on Day 1 of operations, your crews are standing in front of equipment they've never touched, in a yard they've never walked, executing procedures they've only read about on paper.
That's not a training problem. That's a design problem. And it's one that OVRLAI was built to solve.
The Gap Between Construction and Competency
Traditional training models are reactive by design. Equipment gets built. Then training begins. Then crews get certified. Then operations launch — sometimes weeks or months after the window when training could have been most effective.
For mid-sized railroads growing at 10% annually, that lag compounds fast. You're onboarding 50-100 new crew members per year, reconfiguring yards, commissioning new locomotive models, and integrating new signal systems — all while managing day-to-day operations with instructors already spread thin across territories.
The result is a dangerous competency gap that shows up in incident data. The FRA's own research confirms that human factors drive more than one-third of all train accidents, with rail yard incidents showing human involvement in approximately 60% of cases. The most dangerous moment in any operation isn't when crews are experienced — it's when they're new to an environment.
Traditional training can't close that gap fast enough. OVRLAI does it before the environment even exists.
What OVRLAI Actually Does
OVRLAI is A5 Rail's field-deployable augmented reality application built specifically for the railroad environment. Unlike VR systems that require dedicated hardware, controlled spaces, and complex setup, OVRLAI runs on devices your crews already carry — phones and tablets — and works on-site, in the field, in real time.
The core capability is pre-construction visualization and training. OVRLAI overlays digital models of future infrastructure, equipment, and operational environments directly onto physical locations using AR. Crews can walk a yard that's still under construction and see exactly where equipment will be positioned, how switching sequences will flow, and what clearances they'll be working within — before a single rail is laid.
This isn't simulation for simulation's sake. It's practical workforce readiness built into the construction phase itself.
For Directors of Training, it means your certification programs can begin the moment a project breaks ground — not the week before go-live.
For Directors of Safety, it means crews arrive at commissioning day with documented competency in the actual environment, not a generic classroom version of it.
For Directors of Operations, it means Day 1 productivity instead of a 30-60 day learning curve that drains throughput and elevates risk.
The Proof Is Already in the Ground
The Englewood Yard project is the clearest demonstration of what OVRLAI enables at scale. A5 Rail deployed OVRLAI during the construction phase of a complex yard reconfiguration, allowing operations teams to visualize the finished environment, identify procedural challenges before they became operational ones, and begin crew familiarization while the project was still being built.
The insight from that deployment is what every operations leader should hear: the most expensive training mistakes happen after commissioning, when fixing them requires taking equipment offline, retraining crews in live environments, and absorbing the productivity losses that come with it. OVRLAI moves that entire correction cycle upstream — into the construction phase where changes are cheap and incidents are impossible.
Why This Matters for Railroads Growing at 10% YOY
The ICP for OVRLAI isn't every railroad. It's the mid-sized operator — 500 to 1,000 employees, $3M to $20M revenue, growing 10% year-over-year — that is constantly commissioning something new.
That growth trajectory means you're regularly introducing new equipment configurations, new yard layouts, new signal systems, and new crew members who need to reach competency quickly and safely. Traditional training methods assume you have time, dedicated facilities, and available equipment for practice. Growing operations rarely have all three.
OVRLAI removes those dependencies. Training happens in the field, on the actual site, using the actual spatial context crews will work in — even when the physical infrastructure is months away from completion.
This is also a competitive differentiator in workforce recruitment. The FRA's Modal Profile research on railroad workforce trends consistently flags work-life balance and schedule demands as primary friction points for new recruits. Crews who train with modern tools, in modern environments, with instant feedback report higher confidence and faster time-to-competency. In an industry facing 6,600 annual openings driven primarily by retirements, that recruiting and retention edge matters.
The Competitive Landscape Doesn't Offer This
To be direct about where OVRLAI sits in the market: this capability doesn't exist anywhere else in the railroad training space.
Roundtable Learning and their HaptX VR platform require dedicated hardware, controlled indoor environments, and development cycles measured in years — BNSF's eight-module VR training program took more than two years to build. That's purpose-built for classroom environments, not field deployment.
Heartwood 3D delivers strong tablet-based simulation for procedural training, and their FRA waiver for Part 232 Air Brake simulation is genuinely significant. But their platform focuses on screen-based interaction with 3D models — not AR overlaid onto actual physical sites.
Railpros and Axiom, the traditional compliance providers with 3,700+ clients and decades of industry credibility, have no XR capabilities at all. Their strength is compliance documentation, not pre-commissioning workforce readiness.
A5 Rail is the only player in the railroad training market that combines deep railroad operational expertise — including Brent Laing's background as former VP Engineering at CP and CN — with field-deployable AR technology designed specifically for construction-phase training. That combination is what makes OVRLAI a market gap, not just a product feature.
The Total Cost Equation
When Directors of Training build budget cases for OVRLAI, the relevant comparison isn't "cost of AR versus cost of classroom training." It's "cost of AR versus cost of a commissioning-day incident."
The FRA data is unambiguous on what those incidents cost. Typical yard derailments run $10,000 to $30,000. More significant incidents reach $100,000 and above. The East Palestine derailment cost Norfolk Southern over $1.1 billion. Even setting aside catastrophic outliers, the productivity loss from a single crew operating at reduced competency in a newly commissioned environment — slow switching times, procedural errors, near-misses that trigger investigations — compounds quickly against a 10% growth target.
OVRLAI is not a training expense. It's a commissioning insurance policy that pays out before the first incident ever occurs.
From the Director of Operations' chair, there's a parallel calculation: locomotive out-of-service time for traditional training runs "thousands of dollars per minute" according to Railway Age analysis, with minimum full-day downtime per session. Training in AR on a construction site costs zero in equipment downtime because there is no equipment — yet.
What "Ready Before Day One" Actually Looks Like
Here's what OVRLAI deployment looks like in practice for a mid-sized railroad executing a yard reconfiguration or new equipment commissioning:
During the design phase, A5 Rail works with your engineering team to build the digital models that will be overlaid in the AR environment. This is the same process that happened at Englewood — bridging the gap from design to execution before construction begins.
During construction, crews use OVRLAI on tablets and phones to walk the actual site and interact with the future environment. Switching sequences, clearance zones, emergency response positions, and equipment interaction points are all trainable in the physical space before they're physically real.
At commissioning, your crews arrive with documented spatial familiarity, procedural competency, and confidence that typically takes 30-60 days to build through traditional on-the-job experience. The FRA-required competency documentation exists. The safety briefings have happened in context, not in a classroom. Operations launch at capacity instead of ramping toward it.
That's what "ready before Day One" means operationally — and it's a capability that no other vendor in this market currently offers.
Is OVRLAI the Right Fit for Your Operation?
The strongest candidates for OVRLAI deployment share a few characteristics that map directly to the A5 Rail ICP: they're growing, they're regularly commissioning new infrastructure or equipment, they're facing FRA scrutiny that requires documented competency proof, and they've experienced the productivity cost of crews learning in live environments.
If you're managing a yard reconfiguration, a new locomotive class introduction, a signal system upgrade, or any capital project where crew readiness is on the critical path — OVRLAI compresses your risk window and your training timeline simultaneously.
The question isn't whether your operation could benefit from training crews before equipment exists. The question is whether you can afford to keep doing it the other way.
Book a Demo to see OVRLAI in action →
Sources:
• Federal Railroad Administration, Office of Safety Analysis — Human Factors Division (2024) • Association of American Railroads, Safety Statistics 2024-2025 • Railway Age, Training Cost Analysis and Equipment Downtime Research • FRA Railroad Industry Modal Profile: Workforce Trends, Challenges, and Opportunities • Bureau of Labor Statistics, Occupational Outlook Handbook: Railroad Workers (2024) • A5 Rail, Englewood Yard OVRLAI Deployment Documentation