Arcy: Computer Vision and Satellite Imagery for Earth Observation — Deforestation, Insurance, Agriculture

Arcy, a computer vision AI company, deploys vision-language models and change-detection computer vision systems on satellite imagery archives for Earth observation applications. The company works across four key domains: deforestation monitoring, automated insurance damage assessment, AI crop monitoring, and critical infrastructure inspection. In deforestation monitoring, computer vision segments satellite scenes, detects changes such as illegal logging roads and canopy loss, and classifies land cover using temporal image time series from Sentinel, Planet, and commercial satellite constellations. Change detection combined with canopy segmentation forms the core method, while VLMs add text summaries with traceable validated metrics. In automated insurance damage assessment, Arcy processes before-and-after satellite imagery to prioritize and estimate damage at scale following major events. Pipelines co-register scenes, mitigate cloud cover, and assign state classifications (intact, damaged, destroyed) per spatial unit using multi-class classification. In crop monitoring, Arcy tracks vegetation indices over time from high-revisit satellite series to detect stress from water, disease, and pests before visible symptoms appear. VLMs summarise alerts in text while maintaining traceability. In critical infrastructure monitoring, Arcy detects change between dates, segments corridors near linear networks such as pipelines, and identifies geomorphic risk and undeclared works. Arcy partners with Liquid AI for efficient deployable models and DPhi Space for orbital server infrastructure, providing scoping, prototyping on real data, and controlled deployment for production-grade satellite image analysis.