Aspia & Stelia revamp AI for satellite land insight

Aspia Space has partnered with applied AI platform company Stelia to update the architecture behind its Earth observation-derived land intelligence products. The Cornwall-based business aims to improve the speed, cost and governance of large-scale AI workloads.

The collaboration will focus on production systems that process petabyte-scale datasets and deliver real-time outputs for business use. The work centres on performance consistency and data governance, with compliance controls embedded in the platform design.

Earth observation has become a high-volume data source as satellite operators increase revisit rates and improve image resolution. Many organisations, including those with access to commercial satellite data, still struggle to use it in day-to-day operations. The gap often lies between raw imagery and information that fits existing business processes.

Turning satellite data into operational insight requires large amounts of compute, along with data management and governance that can withstand internal scrutiny and external regulation. Companies deploying AI at scale also face challenges around repeatability and accountability. These constraints can slow adoption, particularly in regulated sectors and workflows where teams need confidence in how outputs were produced.

Product focus

Aspia develops land intelligence products from satellite data for sectors including financial services, agriculture, supply chain and the public sector. One product, ClearSky, tracks field variation, biomass changes and crop health trends, and is designed to work even during cloudy growing seasons.

The partnership positions Stelia as a technology partner for the underlying AI architecture. Stelia describes its platform as an "operational backbone" for production AI in high-trust environments, with an emphasis on governed deployment and accountability at scale.

Chris Roberts, Aspia's chief technology officer, said cost and speed have limited reliable AI processing of very large Earth observation datasets.

"Until now, AI workloads delivering reliable and trustworthy insights from petabyte-scale Earth Observation datasets have been prohibitive, both in cost and speed," Roberts said. "Stelia is redefining what is technically possible - allowing the creation and refinement of new models to scale with the speed and sustainability this market demands."

The work is linked to wider industry efforts to move satellite-derived data into operational workflows. The companies cited use cases including disaster risk and insurance assessment, crop and tree monitoring, supply chain optimisation and environmental impact analysis. While these areas have drawn interest from businesses and governments, they often require repeatable analytics and clear governance over data processing.

Architecture shift

Stelia will provide applied AI platform engineering and design systems that can run at large scale. The work with Aspia is expected to improve performance consistency across production deployments and add compliance and governance controls.

The project is positioned as a response to technical constraints in high-performance AI systems used for geospatial data processing. It also aims to support changing customer requirements as organisations expand from pilots to broader deployment across business units.

Kevin Smith, Stelia's chief executive officer, said the company builds AI systems for data-intensive environments and treats regulatory change as a design consideration.

"We engineer AI systems that give our partners a strategic advantage in the most data-intensive environments. They are purpose-built to accelerate product development, adapt to regulatory change, and scale with demand," Smith said. "Partnering with Aspia gives us a chance to apply this approach to one of the most important data frontiers: space, with a company operating at the forefront of the industry."

Aspia plans to use the collaboration as a foundation for new data products built for global scale. Stelia expects its work in the sector to extend beyond platform delivery to contributions on technical standards, regulatory frameworks and responsible AI practices across the space and intelligence ecosystem.