Surface AI and the Future of Airfield Intelligence

Can you list the 20 surface defects with the greatest 30 day change on your airfield, or are you limited to a PCI score that reflects your condition months ago?

At Illuminex AI, we didn’t set out to build a product that only detects FOD. We set out to build a platform, a modular, extensible foundation that helps airside teams see more, know more, and leverage data to act faster.

We started with a focused challenge: Foreign Object Debris detection. FOD poses a direct risk to aircraft safety, and it’s an issue that every airport wrestles with. Our response, FOD AI, was purpose-built as a second set of AI-powered eyes for inspectors, helping log debris consistently, accurately, and under any conditions, with no disruption to existing processes.

But the bigger opportunity wasn’t just spotting debris. It was the operational value of the time series data.

Every image captured by FOD AI is a snapshot of pavement condition. Every run becomes a record. From day one, we designed our InspectEx platform to take advantage of that because we knew that FOD detection was just the beginning.

Now, we’re moving to the next module: Surface AI.

From Incident Logging to Condition Intelligence

Airfields aren’t static, and neither are the problems they face. Cracks don’t wait for scheduled inspections. Surface wear doesn’t stick to an annual PCI cycle. Pavement conditions evolve constantly, and until now, teams haven’t had a reliable way to track that change in real time.

Surface AI changes that.

Built on the same InspectEx platform as FOD AI, Surface AI uses the same edge capture and cloud analysis pipeline. The difference is in what it looks for:

• Cracks

• Depressions and rutting

• Localized degradation patterns

  
  

By pairing ongoing image capture with structured analysis, Surface AI creates continuity. You’re no longer comparing a single inspection run to memory or outdated photos. You’re building a timeline. And that timeline becomes a foundation for smarter decisions: Listing of fastest growing surface defects, when to repair, where to allocate budget, and how to catch problems before they escalate.

As we continue developing our modular inspection suite, we’re expanding beyond just surfaces and debris. Here’s what’s currently in the pipeline:

• Lighting AI: Detect unlit fixtures, bolt checks, and coverage gaps. across edge lights and approach lighting systems.

• Signage AI: Identify faded or missing signage

• Rail Assessment: For airports with rail-based people movers augmenting human rail inspections with sensor-fusion & AI approaches

• Digital Twins: Ultimately, all these modules contribute to a unified, data-rich model of your airfield, a continuously updated digital twin you can use for planning, simulation, and inspection overlay.

  
  

These aren’t isolated systems. They’re interconnected modules, all running on InspectEx, all using the same AI backbone, and all designed to scale with your airport.

Practical by Design

Everything we build is shaped by three design principles:

1. Modularity

You don’t need to install everything at once. Start with one target application. FOD AI. Add Surface AI when ready. Expand to lighting or signage without retraining teams or replacing infrastructure.

2. Operational Fit

We don’t ask you to change your workflows. Our tools plug into what your inspectors already do, capturing the data while they work, not adding more work.

3. Cloud-Driven Insights

All modules feed into a central cloud intelligence layer, making analysis accessible from anywhere, and enabling long-term trend tracking, comparisons, and predictions.

Why It Matters Now

The reality is that infrastructure isn’t getting simpler, and the pressure on operations teams isn’t letting up. Runway usage is climbing. Inspections are critical. And budgets are under more scrutiny than ever.

Predictive maintenance, data-backed planning, and real-time insights aren’t luxuries. They’re the path forward.

By layering FOD AI with Surface AI and eventually Lighting AI, Signage AI, and more, you begin to build an operational intelligence network across your airfield. You start to see patterns. You start to forecast change. And most importantly, you start to shift from reactive to proactive leadership.

What’s Next

We’re currently in development and early testing of Surface AI, moving on to Lighting AI, and Signage AI. We’re validating with airside teams the data advantage.

If your airfield is ready to move beyond isolated inspections and toward a unified view of surface, signage, lighting, and more, we’d love to hear from you.

Let’s talk about where you are now and let’s build the system that gets you where you want to go.