Compare Numina vs. Plainsight

Numina analyzes various activities occurring at curb-level. By collecting data anonymously and in aggregate, the system provides insights into the volume of pedestrian and vehicular traffic, their paths, and overall movement patterns in urban streets. This data aids in assessing detailed traffic safety, environmental factors, and operational metrics within city infrastructures. Additionally, Numina aims to create a data utility that transforms streets into a platform for developers. Upholding privacy as a core value, the design of Numina ensures that its sensors utilize onboard computing to process data while erasing any identifiable imagery, yielding datasets that are both anonymous and secure. It stands out as the only computer vision sensor system specifically tailored for urban environments, having been built from the outset to deliver insights without compromising privacy. While many aspire to create more livable communities, consensus on the best methods often eludes us. Numerous strategies exist for enhancing our neighborhoods, and we are dedicated to assisting cities in arriving at the most effective solutions more swiftly and justly through a data-centric methodology. Ultimately, our mission is to empower urban planners with the information they need to foster vibrant, inclusive spaces.

Streamline your machine learning endeavors with our state-of-the-art vision AI platform, designed specifically for rapid and efficient development of video analytics applications. Featuring intuitive, no-code point-and-click functionalities all within a single interface, Plainsight significantly reduces your production time and enhances the effectiveness of vision AI-driven solutions across various sectors. Manage and control cameras, sensors, and edge devices seamlessly from one platform. Gather precise training datasets that lay the groundwork for high-quality model training. Speed up the labeling process through advanced polygon selection, predictive labeling, and automated object recognition techniques. Train your models effortlessly with a revolutionary method aimed at minimizing the time required for vision AI implementations. Moreover, deploy and scale your applications swiftly, whether at the edge, in the cloud, or on-premise, to fulfill your business requirements effectively. This comprehensive approach not only simplifies complex tasks but also empowers teams to innovate rapidly.