Compare Helm.ai vs. Vecten Desktop

We provide licensing for AI software that spans the entire L2-L4 autonomous driving framework, which includes components like perception, intent modeling, path planning, and vehicle control. Our solutions achieve exceptional accuracy in perception and intent prediction, significantly enhancing the safety of autonomous driving systems. By leveraging unsupervised learning alongside mathematical modeling, we can harness vast datasets for improved performance, bypassing the limitations of supervised learning. These advancements lead to technologies that are remarkably more capital-efficient, resulting in a reduced development cost for our clients. Our offerings include Helm.ai's comprehensive scene vision-based semantic segmentation, integrated with Lidar SLAM outputs from Ouster. We facilitate L2+ autonomous driving capabilities with Helm.ai on highways 280, 92, and 101, which encompasses features such as lane-keeping and adaptive cruise control (ACC) lane changes. Additionally, Helm.ai excels in pedestrian segmentation, utilizing key-point prediction to enhance safety. This includes sophisticated pedestrian segmentation and accurate keypoint detection, even in challenging conditions like rain, where we address corner cases and integrate Lidar-vision fusion for optimal performance. Our full scene semantic segmentation also accounts for various road features, including botts dots and faded lane markings, ensuring reliability across diverse driving environments. Through continuous innovation, we aim to redefine the boundaries of what autonomous driving technology can achieve.

Vecten Desktop is a specialized software designed for the classification of LiDAR point clouds generated from both airborne and UAV surveys. It streamlines workflows by categorizing tasks into local projects and blocks, allowing for the input of LAS, LAZ, and COPC file formats, and generates classified point clouds complete with review layers and attributes for verification and subsequent handoff. The software features VGround for identifying ground surfaces, bridge decks, and noise, while VClassify focuses on vegetation and building identification; additionally, VUtilities addresses wires, poles, and towers specifically for utility corridors. Different teams in surveying, mapping, engineering, and utility sectors can choose from various modules based on their specific output needs for terrain extraction, semantic classification, infrastructure analysis, or corridor asset management. The classification process is efficient and takes place on a local workstation, eliminating the need for cloud-based uploads for inference. Furthermore, there are plans for Vecten Cloud, which will serve as a browser-based companion tool, and interested users can join the waitlist for future access. This expansion reflects the commitment to enhancing accessibility and functionality for users across various industries.