How we built a flexible, scalable and user-focused product for Airspace Data

Airspace Data: Delivering a Properly Calibrated MVP | Foxbox Digital

United States airspace spans a staggering 

 square miles. Of that amount, approximately ¼ is reserved for use by the military for training and testing of aircraft, new technologies, and advanced weapons.

Who occupies that space at any given moment is the result of close communication between the FAA, airline dispatchers and the US Department of Defense. With 45,000 commercial and civilian flights traveling through US airspace every day, even the most seemingly incremental improvements to this process can create a profound positive domino effect.

Airspace Data is a technology company aiming to do exactly that.

The short of it: Airspace reserved for the military is often unoccupied. But without a real time view of that valuable airspace, the FAA, the airlines, and private pilots can’t utilize it.  Similarly, the military increasingly needs access to civilian airspace, and needs a better way to make those requests.

By equipping military-range operators, the FAA and airline dispatchers with the precise, timely data indicating the availability of military-controlled airspace, 

Airspace Data helps airlines plan routes more efficiently

 - leading to lower carbon emissions, faster flights, reduced fuel costs, and the type of dynamic transparency that elevates the aviation industry as a whole.

The military sees reduced manual workload in its communications with FAA, and enhanced mission readiness for key training and test objectives.

Having gained early traction with major US airlines, a web-based MVP became the critical missing piece Airspace Data leadership needed. They looked to Foxbox to get it off the ground.

Building our solution with the military, FAA, and the airlines happens in scarce,  high-stakes meetings. I can’t bluff my way through it, the product has to work. So what Foxbox did is really important because it does. It works.

Understanding, contextualizing and interrogating the problem was top priority.

Through a combination of collaborative workshops, user interviews, and design exploratories, our team gathered the pieces necessary to bring the puzzle into focus. While the client’s existing proof of concept and strategic vision helped us ask the right questions, we sought a first-hand perspective to find the right answers.

Alongside Airspace leadership, members of our UX and Product Strategy team visited with all stakeholders to deepen our contextual understanding and help inform upcoming interviews with airline dispatchers. One such interview revealed a pivotal flaw in our underlying assumptions.

“Having access to this type of data would be a game-changer,” one dispatcher said, “but not for my role.”


At their particular airline, the dispatcher explained, the 

would glean much more direct value from the tool.


While just one step upstream in the flight planning process, reframing the product strategy to serve both navigation analysts and airline dispatchers became critical to ensure we built the right thing the right way.

Without that understanding of who's really going to use it, we would have completely missed the mark.

We built a detailed product roadmap, outlining how to serve both navigation analysts and dispatchers, as primary and secondary users respectively. Our team of Product Specialists and UX / UI designers then began to bring product concepts to life. Early low fidelity design mockups allowed us to elicit feedback from both Airspace Data leadership as well as the airline stakeholders we had now more precisely defined.

Because no two airlines operate the same way, and no two navigation analysts / dispatchers within those airlines focus on the same regions of airspace, a rapidly iterative design process helped us bring a methodical approach to the product’s central challenge: The user experience needed to be 

robust enough to manage the totality of relevant US airspace data, yet simple enough to fit seamlessly into existing route planning workflows.

Recognizing that our solution would introduce an additional step, pinpointing the role of user notifications became central to our ability to craft a seamless and impactful user experience. 

With an emphasis on simplicity and precise communication, the Airspace Data interface minimizes cognitive load, while maximizing the type of context-dependent, time-sensitive information users require. Optimizing for simplicity also meant deliberately avoiding a map-centric format, in favor of a focused interaction model that mirrors the needs, preferences and priorities of both primary and secondary users.

 Working in close collaboration with Airspace Data’s technical leaders, we moved high-fidelity designs into production.

For our team of front end developers, engineers and QA specialists, success depended on a combination of continuous end-to-end testing, automated deployments and an ability to navigate the industry’s unique complexities and existing data infrastructure.

Airspace Data 1.0 was released to both commercial airlines and cargo carriers in December 2023. Version 2.0 was completed with the help of ongoing Foxbox development support in April of 2024, and is already being received very positively by major US Airlines.      

 For airlines engaging in city pair trials, the financial and environmental impact of the product is already on full display. The company and its airline partners have completed more than 2,700 flights, saving 2 million pounds of CO2 emissions, 60,000 flight miles, and 100,000 gallons of fuel.


With a product properly rooted in the end user’s perspective, Airspace Data Leadership is now better equipped than ever before to focus on building new customer relationships, expanding  to new users, and evolving revenue models to best position the company for long-term success.

Foxbox was crucial to our ability to stay agile

Airspace Data VP of Engineering George Song

Foxbox built the Airspace Data web application with the following technologies:

Airspace Data: Delivering a Properly Calibrated MVP

The democratization of software, product strategy, and the case for proper experimentation. 

Generative AI is making it easier than ever to build the wrong thing

Generative AI is making it easier than ever to build the wrong thing.

"The democratization of software” long promised by no-code software and AI-enabled development tools is soon to actually arrive, thanks to ChatGPT and AI development tools like GitHub Copilot. Businesses of all sizes can undoubtedly benefit from the ability to build digital products in a fraction of the time. But the problem is this: 

The decisions that shape high performing digital products are made long before a line of code is written.

So while the path to building and launching a product might be faster than ever, generative AI tools can also act as a high-speed train to the 

So how do you build the right thing? Here’s a few things to keep in mind.

It’s easy to fall in love with a slick interface. We’ve all done it. And the next wave of generative AI tools will only compound the problem.


When a few prompts and shiny drag and drop tools can churn out UX & UI mockups or even functional applications, it’s easy to create a digital product that appears well-designed on the surface, but whose foundation is shaky at best.

For the same reason you’d never design a car around the upholstery, AI-powered development tools can be your friend, but not as a replacement for things like user research, persona development, technical assessment and competitive landscape analysis.



Particularly when development can be so dramatically accelerated, the ability to test, experiment and challenge your own assumptions is more critical than ever. When building a digital product, being wrong early is a gift.


It’s how we discover that there’s more nuance to various target users than initially assumed. It’s how “happy paths” emerge through careful research and usage analysis. It’s how refined product roadmaps clarify the future development plan that mitigates cost while still making substantial progress.


Don’t squander the gift of being wrong early in the name of being done fast.

The age of generative AI will make the gap between the two wider than ever. A well crafted digital product solves the right problem the right way. Which takes an intimate understanding of your business, your customer and broader cultural context that AI will fall short of reaching.


When it’s easier than ever to build the wrong thing, we’ll see a proliferation of software in search of a problem to solve. Perhaps circling the problem, even approaching it or pointing to it, but not built soundly enough from the jump to actually solve it.


So should you invest in AI tools capable of writing software? Sure.


But remember: software’s not really what you’re after.

Ready to learn more about building a practical AI roadmap for your organization? Join our  free workshop: AI Roadmaps for the Real World on LinkedIn Live on April 18th.

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2 posts tagged with “uxdesign”

Airspace Data: Delivering a Properly Calibrated MVP

Generative AI is making it easier than ever to build the wrong thing