dida develops In-terra-gate: new approaches to satellite data analysis with natural language

dida is pleased to announce “In-terra-gate”, our latest project to transform satellite data analysis through natural language interaction. This initiative uses advancements in large language models (LLMs), natural language processing (NLP), and visual foundation models to create an intuitive tool that translates complex satellite data into actionable insights. The project is an ESA Kickstart Activity and enables users to query geospatial information using natural language, providing accurate answers about geological and geographic features in satellite imagery.

In-terra-gate uses text-image embeddings trained on high-resolution Sentinel-2 satellite data to provide insights into urban areas, residential zones, and regions exposed to natural hazards. This tool was developed with insurance companies in mind, as they need accurate, real-time data to assess individual property risks and expedite claims, e.g. for homeowners and farmers. With In-terra-gate, dida is setting a new standard in satellite data accessibility, providing non-technical users with the opportunity to intuitively harness the potential of complex satellite data analysis in various scenarios and industries.