Zurich-based aviation technology company Assaia has recently secured $26. 6 million in a Series B funding round, with Armira Growth as the lead investor. This funding round was oversubscribed, with existing investors also participating.
As air traffic volumes have returned to pre-pandemic levels and airports are facing staffing constraints and tighter operational margins, there is a growing focus on intelligent automation in the aviation industry. Assaia’s AI platform supports this shift by streamlining turnaround times and improving planning for airside operations.
Using artificial intelligence and computer vision, Assaia provides airports and airlines with full visibility and control over aircraft turnaround operations. Its solutions can predict potential issues, automate key processes, and enhance operational performance, leading to safer, faster, and more sustainable airport environments.
CEO Christiaan Hen stated that this funding marks an important milestone for the company, as airports and airlines are increasingly turning to AI to address operational challenges. With the support of Armira, Assaia plans to accelerate the adoption of new technologies and expand its global presence, delivering measurable value in complex airport environments.
Assaia’s technology, designed to optimize the aircraft turnaround process through real-time visibility and automation of apron operations, is already in use at major international hubs such as New York JFK, London Heathrow, Dubai International, and Toronto Pearson. These airports have seen reduced delays, improved on-time performance, and better gate utilization thanks to Assaia’s solutions.
The newly acquired funding will enable Assaia to further scale its AI platform globally and launch additional solutions aimed at improving efficiency for airports, airlines, and ground handlers. A portion of the funding will also support the rollout of StandManager, a planning module that uses AI to optimize gate and stand assignments before the aircraft lands, improving predictability and gate utilization in crowded and high-volume environments.