Based in Germany, OroraTech has developed an AI-powered wildfire monitoring platform that combines thermal data from over 25 satellites to provide timely alerts, fire behaviour forecasts, and post-event assessments.
The system is already in use across multiple continents, including in Chile, Canada, Australia, and several EU Member States. The platform also models how fires are likely to evolve based on weather and terrain conditions, supporting both immediate response and short-term risk forecasting. This capability allows emergency services to anticipate the spread of fires, optimise resource deployment, and prioritise evacuations.
OroraTech reports over 500 users in 25 countries, including forestry and civil protection agencies that use the platform to enhance situational awareness and operational planning. Users have identified four main benefits: faster mobile alerts, improved accuracy of fire spread simulations, flexible data integration, and efficiency gains through automation.
“The feedback we hear most often,” says Gottfriedsen, “is that these capabilities save time, improve accuracy, and build the trust needed to scale new technology in high-stakes wildfire management.”
AI lets us move from reactive to proactive wildfire management. But public adoption still depends on trust, interoperability, and proof of accuracy.”
The platform’s data now contributes to the Copernicus programme, after OroraTech was selected as one of nine Emerging Copernicus Contributing Missions. The company is also working with governments, including Greece, which in 2024 launched a national satellite-based wildfire early-warning system supported by OroraTech data.
By combining AI with satellite-based observation, such systems are helping civil protection services act earlier and with greater precision. However, their integration into operational workflows still depends on interoperability with national systems, user training, and continued confidence in the quality of AI-generated information.
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