Revolutionising the Drone Industry
Envision a future where drones effortlessly navigate complex airspace without colliding with other drones or objects, all while providing essential services to society. Skypuzzler’s integrated Digital Air Traffic Control (iDATC) enables drones to fly safely by providing clear paths and instructions through software-to-software communication without extra equipment to be installed on the drones.
As the drone industry grows, there is a rising concern about flight safety and increasing demand for scalability to fly drones Beyond Visual Line Of Sight (BVLOS) to ensure business viability. To meet these concerns and demands, advanced Unmanned Traffic Management (UTM) systems are crucial to ensure flight safety and scalable operations.
Skypuzzler’s iDATC, is an integrated module to advance UTM systems, enabling the UTM systems to manage the complexities of all drone operation scenarios safely and efficiently.

Developed by air traffic controllers with flight safety embedded in their DNA and experienced computer scientists rooted in deep tech.
Recognised Award Winner
CASSINI Challenges 2024
Skypuzzler has proudly secured the Product Track Prize of the European Union Agency for the Space Programme’s (EUSPA) CASSINI Challenges.

Air Traffic Management Award 2022
Skypuzzler has already demonstrated its commitment to revolutionising the aviation industry by winning the Air Traffic Management (ATM) Award in the category ‘Shaping our future skies’, making it the first startup to receive this award.

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Latest news and updates

Skypuzzler attends the European Network of U-space Stakeholders Meeting
Tomorrow, Jesper Skou and Sebastian Babiarz will attend the European Network of U-space Stakeholders Meeting in Hamburg.

Meet Skypuzzler at the International Drone Show (IDS) 2025
Several Skypuzzler team members will attend IDS in Odense, Denmark, on Wednesday June 18 and Thursday June 19.

AI is a great tool when used for non-safety-critical methods
With AI being a significant tool for companies and individuals, Morten Skov and Fredrik Holsten deem it essential to distinguish between data-driven and mathematical models when speaking of AI.