CORE BUSINESS
EarthLab Luxembourg S.A., a member of the Telespazio group, is an innovative company strategically based in Luxembourg, EarthLab operating at the intersection of geoinformation and ICT. As a leader in Earth observation data processing and AI, EarthLab is dedicated to advancing capabilities in various domains, including defense intelligence and smart farming. The company excels in automating Earth observation data processing and leverages Big Data, Artificial Intelligence, and cybersecurity to drive innovation.
EarthLab develops and commercializes the Max-ICS platform, a secure and scalable Earth Observation Data Processing and AI-as-a-Service solution. Designed to facilitate the creation and deployment of sophisticated Deep Learning and Machine Learning models within complex processing chains, Max-ICS features a hybrid-cloud and big-data infrastructure.
This enables seamless integration of diverse data sources, especially satellite Earth observation data
PRODUCTS & SERVICES
We commercialize Max-ICS platform: a highly flexible and data-centric platform that allows dealing with the landscape of global risks. Our solutions are built on high-performance computing to support decision-makers in the event of risk manifestations, providing detailed, timely, and relevant information.
A key advantage is that there is no ICT workload to set up, configure, and maintain with our platform. We provide a dynamic vulnerability scoring in terms of operations, the resilience of communities, supply chain, and environment. We use in-house simulations and A.I. models to anticipate the next landscape of significant risks. We enrich risk models by creating information thanks to automatic recognition into massive datasets to give context to risk assessment. We also aggregate thousands of datasets from social and economic indicators in real-time, allowing us to predict the consequences of extreme situations (natural disaster, endemic accident, political event, pandemics, etc.).
TECHNICAL MEANS
EarthLab Luxembourg implements its products and services, relying on its private infrastructure. The implemented technologies follow the “Big Data” paradigms and fully subscribe to an elastic model ensuring future large-scale capacities.
Our approch relies on four different pillars: (1) strong data engineering and analytics, (2) data modeling and application of state-of-the-art A.I. algorithms, (3) optimization and automation with our Max-ICS platform and, finally, (4) an agile approach when building solution or project analytics.
MAIN CUSTOMERS
The current EarthLab Luxembourg’s client base is insurance, financial services, industrial companies, and brokers about environmental risks and large industrial complexes concerning endemic hazards. We are acting in the open-source and open data communities to share data science knowledge for communities.
MAJOR SPACE PROJECTS
DTE Highway
The project is part of the European Commission’s Destination Earth (DestinE) initiative, which aims to develop detailed Digital Twins of the Earth (DTE) for advanced monitoring and simulation of natural and human activities. The ESA DTE component Highway will provide access to ESA Earth Explorer data for integration into these digital twins, with Maxi-ICS handling the OnDemand data processing.
DT4CMI
The project aims to transform cocoa farming by using the Max-ICS platform with satellite data and communication tailored to the terrain. It will enhance monitoring and improve crop yield, offering substantial economic benefits for farmers.
Maritime Surveillance
It is crucial to analyze the surface activities & the comportment in dark-fish or preservation of protected maritime areas. E.O., GNSS, & A.I.are very important: it offers the possibility of systematically analyzing all the area images. Max-ICS platform helps create or improve the A.I. models & supports the automatically scaled deployment within a public cloud
DroneAI
EarthLab has launched an innovative solution to push the use of space data and A.I. on disaster/humanitarian response: it combines E.O. open & commercial data to feed a data processing chain defined by the actors
