LayerNext is an AI data infrastructure tool specifically designed for computer vision (CV) projects. It offers a comprehensive suite of features to help AI teams collect, curate, label, and search large-scale CV datasets. With LayerNext, users can efficiently manage their training datasets with version control, making it easier to develop and iterate on models. One of the key features of LayerNext is its DataLake, which serves as a unified repository for all AI data. This includes raw images and videos, curated data, ground truth, and model outcomes. The DataLake provides a built-in viewer, allowing users to visualize their data in one place and easily search and explore it.
LayerNext also offers annotation tools through its Annotation Studio, enabling users to label image and video data at scale. The platform includes built-in analytic tools to help analyze the effectiveness of training data, identify data gaps, and address model and label errors. The tool emphasizes collaboration and integration, offering SDKs and APIs for seamless integration with other computer vision applications and services. LayerNext also provides specialized apps for processes such as curation and annotation, allowing for streamlined workflows.
LayerNext is self-hosted by default, providing users with control over their data and ensuring compliance with regulations such as HIPAA and GDPR. The flexibility and security of LayerNext make it suitable for various industries, including retail, agriculture, healthcare, and construction. Overall, LayerNext aims to enhance AI team productivity and collaboration by providing purpose-built data tools and automated workflows for computer vision projects. Its user-friendly interface and comprehensive features simplify the CV workflow, enabling teams to focus on the core aspects of their AI projects.
