OpenAtlas builds geospatial intelligence systems that leverage satellite imagery and AI to monitor global supply chains and agricultural operations. The platform provides deforestation monitoring and traceability analysis for complex remote sensing challenges. This service enables businesses of all sizes to cost-effectively meet regulatory compliance obligations like the EUDR.
Funding
Funding not disclosed
Founders
Product
Problem
Businesses importing commodities into the EU face increasing pressure to ensure their supply chains are deforestation-free due to regulations like the EU Deforestation Regulation (EUDR). Verifying the origin of commodities and monitoring land-use changes across global supply chains is complex and costly, especially for small and medium-sized enterprises (SMEs). Many businesses lack the tools and expertise to accurately assess deforestation risks and comply with evolving regulatory requirements.
Solution
OpenAtlas provides a satellite-based deforestation monitoring solution that helps businesses comply with the EUDR by leveraging remote sensing and AI-driven analysis. The platform combines high-revisit satellite imagery with proprietary machine learning algorithms to detect and track changes in land use with high accuracy. OpenAtlas enables businesses to monitor their global supply chains, assess deforestation risks, and ensure that imported commodities do not originate from deforested land. The solution offers scalable and cost-effective deforestation detection, integrating easily into existing traceability platforms and ERP systems. By providing verifiable evidence of deforestation-free sourcing, OpenAtlas helps businesses meet compliance obligations and mitigate risks associated with deforestation.
Target Audience
OpenAtlas primarily serves businesses importing commodities into the EU, particularly those dealing with soy, beef, palm oil, cocoa, coffee, rubber, and wood, as well as traceability providers seeking to enhance their offerings with satellite-based monitoring.
Features
- Deforestation detection using deep-learning self-supervised learning (SSL) models
- Satellite imagery analysis for monitoring land use changes in global supply chains
- Integration with existing traceability platforms and ERP systems via API
- Automated risk scoring and reporting based on deforestation monitoring data
- High-resolution remote sensing for accurate deforestation detection
- Above-Ground Biomass (AGB) estimation using ML-powered Sentinel-2 modelling
- Dynamic prediction infrastructure via Google Earth Engine