Spoor´s software uses cutting-edge computer vision and AI to detect, track, and classify birds in wind farms to help developers and operators gain insights and guide mitigation measures. We have built a unique approach to object detection based on motion and is a world-first and patented technology. We use a combination of computer vision, image processing, and AI models. This allows us to work with multi-modal (RGB and thermal sensor), high-resolution images (for range) and run our algorithms in real-time applications. Our custom detection-tracking-classification algorithm is cutting-edge, modular, incorporating multiple spatial and temporal ML models, and can run in the cloud as well as real-time on the edge. We use a modern agile development approach to build and host our system in a cloud-based environment and have access to cutting-edge cloud services, hardware, storage, and compute resources for development of AI models.

The unique benefit of Spoor’s system – in comparison to available alternatives like thecombination of high-specification cameras, radars, and human observers – is that the company’s AI technology has been developed to accurately identify and track birds specifically. The Spoor system has no blind spots and is significantly more cost-effective than the alternatives.

At Spoor, we are 100% focused on developing software that enables the wind industry to measure and report on bird impact, operationalise analysis, and implement deterrent measures. Spoor is a rapidly growing Norwegian AI start-up which already has multiple projects installed offshore with major renewables developers. Spoor aims to set the standard for the ecologically responsible development and operation of offshore windfarms, and its mission is to enable industry and nature to coexist. Spoor's three co-founders met in 2020 during Antler's venture capital start-up programme in Oslo.