Get the Answer, Without Ever Seeing the Data

AIR Lab Singapore and HintSight Technology Lay the Groundwork for a New Model of Data Sharing in Aviation

Aviation runs on collaboration, and collaboration runs on data. Airlines, air navigation service providers (ANSPs) and other stakeholders each hold information that could help the others plan better, respond faster and operate more efficiently. Yet much of it stays where it is. Commercial sensitivity, data sovereignty and regulation mean that even when everyone would benefit from sharing, doing so is rarely straightforward.

For years, the industry has lived with a trade-off: share the data and give up control of it, or protect it and lose the benefits of working together. AIR Lab Singapore and HintSight Technology set out to test whether it must be a trade-off at all.

The Technology: Computing on Locked Data

The approach is Fully Homomorphic Encryption (FHE), a cryptographic technique that allows computation on encrypted data without ever decrypting it. Stakeholders can collaborate on analytics and decisions while their raw data stays under their own control.

The core operation is called a homomorphic comparison: asking “Is A greater than B?” The server never sees A or B; it only processes encrypted inputs and returns an encrypted answer. Even the platform performing the computation cannot read the data it is working with.

Putting it to the Test: A Hypothetical Scenario

To prove the architecture, the PoC used a deliberately simple, hypothetical scenario built around a commercially sensitive figure: the fuel remaining on an aircraft. When a controller is deciding whether an aircraft can hold before landing, the key question is whether it has enough fuel. The airline has that number and the controller needs it, but it never leaves the airline’s systems.

In practice: the airline encrypts its fuel figure before it leaves its system. The platform receives a locked value and runs the comparison directly on it, checking it against the fuel required for each operational scenario. The result comes back as an encrypted YES or NO that only the controller can decrypt. No one in the middle ever sees the fuel number.

The proof of concept worked end to end. In the final demonstration, a holding-feasibility query was answered in about 1.4 seconds on a single CPU core, fast enough for the window in which the decision is actually taken.

The fuel scenario was chosen as a clean, well-bounded problem to prove the architecture, not as an end in itself. The same building blocks, i.e. encryption, encrypted evaluation and decryption, can be applied to other commercially sensitive data, from payload and maintenance status to operational KPIs that could be benchmarked across airlines and ANSPs without any party revealing its raw numbers.

Part of a Bigger Mission: Regional Collaboration

This PoC sits inside AIR Lab’s broader push to make Asia-Pacific air traffic management more connected. At its core is RCP, the Regional Collaboration Platform, which already links ANSPs across the region and faces the same obstacle as the rest of the industry: coordination requires data, and data is rarely shared freely.

FHE changes that equation. It allows the computation to happen without the disclosure, which makes it a natural fit for what RCP was built to do: help the region’s ANSPs work together without asking anyone to give up control of their own data.

What This Means

FHE doesn’t eliminate the need for data. It changes what has to be exposed to make a decision.

Airlines keep their numbers. Controllers get the answer they need. The platform runs the calculation without ever seeing the input.

If that model holds across the use cases identified, the question shifts. It is no longer whether stakeholders will share their data, but how much faster ATM innovation can move once they no longer have to.

The Bigger Picture

Every stakeholder has good reasons to protect what they hold, and no single actor can solve that alone. But this PoC is a reminder that the barrier isn’t always trust or willingness; it’s often just the tools available. Collaboration and innovation, applied to the right problem, make it possible, turning long-standing obstacles into real progress.

About HintSight

HintSight is a deep-tech company specialising in Fully Homomorphic Encryption. Their expertise lies in bridging the gap between advanced cryptography and real-world applications, designing FHE-based solutions that are both technically rigorous and operationally viable. For this proof of concept, HintSight brought the cryptographic know-how that made privacy-preserving computation on sensitive aviation data possible.