Spain's Xoople secures $130 million to develop the data infrastructure required for AI to comprehend Earth.

Spain's Xoople secures $130 million to develop the data infrastructure required for AI to comprehend Earth.

      In summary, Xoople, a geospatial data firm based in Madrid and established in 2019, has secured $130 million in a Series B funding round led by Nazca Capital. This funding has increased its total capital raised to $225 million, elevating its valuation to unicorn status. Other investors in this round included MCH Private Equity, CDTI, Buenavista Equity Partners, and Endeavor Catalyst. Additionally, Xoople announced a collaboration with the US defense contractor L3Harris Technologies to develop sensors for its own satellite constellation, aimed at producing Earth surface data that it claims will be "two orders of magnitude better than existing monitoring systems." Xoople's EarthAI platform, which operates on Microsoft Azure and is offered through Microsoft and Esri, provides continuous surface intelligence for various sectors, including insurance, agriculture, government, and infrastructure.

      Over the past seven years, Xoople has created a commercially deployable continuous, AI-native data layer for Earth's surface. The Madrid startup, launched in 2019, has emerged from this development phase with €115 million in prior funding, a platform integrated into the two leading enterprise geospatial ecosystems globally, and a belief that the AI era requires a new approach to Earth observation—specifically tailored for machine learning rather than adapted from traditional satellite imagery workflows. The $130 million Series B led by Nazca Capital confirms that investors find this belief convincing enough to support it on a larger scale.

      Fabrizio Pirondini, CEO and co-founder, shared with TechCrunch that the latest funding brings Xoople’s total to $225 million, establishing its unicorn status. Other contributors to this round included MCH Private Equity, CDTI, Buenavista Equity Partners, and Endeavor Catalyst.

      What EarthAI does

      Xoople's primary product, EarthAI, serves as an end-to-end Earth intelligence system. It continually ingests surface data from government spacecraft and third-party satellite networks, transforming it into AI-ready datasets for change detection, risk prediction, and environmental monitoring. The significant design focus is on continuity: EarthAI is engineered to provide a persistent, structured overview of the Earth's surface rather than discrete images for human evaluation.

      The applications of EarthAI span multiple industries reliant on understanding Earth's physical surface. In agriculture, it allows early detection of crop stress, monitors soil health and water conditions, and provides data for farmers to access carbon credit markets. In insurance, it improves climate risk pricing accuracy and enables real-time verification of natural disaster claims, eliminating delays and biases from ground assessments. For infrastructure operators, it tracks physical assets for signs of stress or deterioration before failures occur. Government entities can leverage it for emergency planning, environmental enforcement, and humanitarian responses. The influx of capital into specialized AI applications at the intersection of science, data, and infrastructure has surged over the past year, positioning Xoople squarely at this intersection.

      The satellite initiative

      The $130 million funding will facilitate Xoople’s shift from relying on external data sources to generating its own. Along with the Series B, the firm announced a partnership with L3Harris Technologies to design and produce sensors for its satellite constellation, which will gather optical data. Pirondini indicated to TechCrunch that the constellation aims to generate "a stream of data that is going to be two orders of magnitude better than existing monitoring systems," which, if proven true, would significantly enhance the quality of imagery currently available from commercial Earth observation operators.

      This claim presents a competitive challenge for Xoople as it enters a market populated by Vantor (formerly Maxar Intelligence), Planet Labs, BlackSky, Airbus Defence and Space, ICEYE, and Capella Space—all possessing operational satellites and established AI data processing frameworks. Firms creating the hardware and data layers essential for AI often encounter a lengthy gap between announcing innovations and delivering them in a usable form, and Xoople's satellite constellation has yet to be launched. Presently, EarthAI relies on data it does not produce. The partnership with L3Harris indicates that acquiring proprietary data is the forthcoming phase.

      Distribution ahead of data

      Xoople’s approach is atypical for an Earth observation company. While most competitors have focused initially on hardware by launching satellites, Xoople reversed this trend by spending its initial seven years integrating its platform into the services of Microsoft and Esri, the two leading software environments favored by enterprise clients, governments, and GIS experts. Neither Microsoft nor Esri has proprietary satellite data, positioning Xoople to fill this void within the platforms where purchasing decisions are made.

      Xoople’s relationship with Microsoft is foundational, as its platform operates on Azure and integrates with Microsoft’s Planetary Computer Pro, which delivers AI-powered geospatial insights for corporate use. Esri, the biggest geospatial software company worldwide, serves as a distribution partner. This suggests that once Xoople's satellite constellation becomes operational and delivers on its data quality promise, it will have distribution capabilities that newer competitors would take

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Spain's Xoople secures $130 million to develop the data infrastructure required for AI to comprehend Earth.

Madrid-based startup Xoople has secured $130 million in a Series B funding round led by Nazca Capital to develop its own satellite constellation and EarthAI platform for ongoing Earth monitoring.