Klayo's product development is guided by one principle: the platform should reflect how airports actually work, not how software companies think they should. We spoke with Jason Theofilos, Head of Product at Klayo, about what workforce intelligence means in practice, how product decisions are made, and where the platform is heading.
Klayo is described as a "workforce intelligence" platform. What does that term actually mean, and how is it different from workforce management?
It is the difference between knowing that you have 200 employees and knowing whether those 200 employees have the right capabilities for what the operation needs tomorrow, next quarter, or next year.
Workforce management is typically about the mechanics: scheduling, time tracking, payroll, rostering. Those are important, but they do not answer the strategic questions that airport leaders are increasingly asking. Workforce intelligence is about connecting the dots between people, skills, roles, training, compliance, and operational needs in a way that gives you actionable insight.
That distinction matters enormously in airports, where regulatory requirements, safety standards, and operational complexity make the "who can do what" question more consequential than in most industries.
How does the team decide what to build?
Everything starts with a real operational problem. We do not build features because they look good on a product page, we build them because an airport has told us, or shown us, that something is not working. A lot of our roadmap comes directly from implementation conversations, where we are working alongside airport HR teams, training managers, and operations leaders and seeing firsthand where the friction is.
The other input is pattern recognition. When we see the same challenge appearing across multiple airports in different regions, that tells us it is a structural problem, not a one-off. Those patterns are what shape our priorities.
Can you give an example of a feature that came directly from that kind of input?
The whole origin of the platform comes from that input. Through working with airports across the Online Learning Centre, we kept hearing that they could tell you who had completed a training course, but they could not tell you whether that training was even needed, whether it was linked to a compliance request or how it would affect the employee skills and role performance.
Completion and competency are not the same thing. So we built a capability that shows, in real time, which employees are fully qualified, partially qualified, or not yet qualified for specific roles, and what the gaps are. That changes how managers make deployment decisions, because instead of assuming everyone who finished a course is ready, they can see exactly where the gaps remain.
AI, Data, and What Comes Next
There is a lot of talk in the industry about AI and predictive analytics. How does Klayo approach that?
We are deliberate about it. The hype around AI is enormous, but in a regulated, safety-critical environment like an airport, you need to be very intentional about where and how you apply it and in ensuring that AI accelerates and enables but does not hallucinate.
For us, AI has to solve a real operational problem and provide trustworthy outputs, not just sound impressive on a product page.
Klayo Intelligence is a good example of how we think about this. It is our AI-powered feature built on exclusive industry data that allows airports to create industry-standard job descriptions in minutes, or to benchmark their existing roles against our library of airport-specific standards. That is not AI for the sake of AI. It is a practical capability that saves airports significant time and gives them confidence that their job frameworks reflect genuine industry best practice.
Beyond that, we also see AI playing an increasingly important role in how training content is built and developed. The way courses are designed, updated, and personalized is going to change significantly in the coming years, and it is something we are actively exploring to make sure we always bring the best capabilities to our airport partners.
But the foundation has to be right first. If your workforce data is fragmented or incomplete, layering AI on top of it does not solve anything. It just gives you faster bad answers. So our priority remains making sure airports have a clean, connected, real-time view of their workforce, because that is what everything else depends on.
Where is the platform heading over the next year?
We are investing heavily in bringing more of the workforce experience into a single, connected platform. Right now, there are still too many places where airports manage workforce data in one system, training in another, compliance in another, and career development in yet another. That fragmentation is the root cause of most of the visibility problems our customers describe.
Our direction is to close those gaps, to build a platform where workforce intelligence, training alignment, compliance management, and employee development all live in the same place, speaking the same language. We are not far from that, and I think the airports we work with are going to see a meaningful step forward in the coming months.