Case Study: Sunflower Labs achieves safe autonomous drone flights with Meteomatics' high-frequency Weather API

Safe Autonomous Flying – Thanks to Data from Meteomatics’ API

Sunflower Labs, a provider of autonomous outdoor drone security systems, faced the challenge of autonomously determining whether planned flights are safe under highly variable local weather — especially precipitation, wind and hail — and needed hyperlocal, frequently updated forecasts. To meet this requirement Sunflower Labs turned to Meteomatics and has been using the Meteomatics Weather API since August 2021 to feed its flight-planning and safety decisioning.

Meteomatics delivers hyperlocal real-time and forecast data (including wind speed, gusts, temperature, hail and precipitation at a 5‑minute interval) via a single, easy-to-integrate API endpoint with sub‑5‑minute update frequency. By using Meteomatics, Sunflower Labs improved the accuracy and timeliness of its go/no‑go flight decisions, kept drones flying safely and on schedule, and gained weather-driven insights for predictive maintenance across different environments.

Sunflower Labs

Yannik Nager

Robotics and Machine Learning Engineer