Encord is a top choice for ML teams working with multimodal, regulated, or large-scale data, offering a full-stack approach to annotation, data management, model evaluation, and QA workflows. SuperAnnotate is designed for speed and team collaboration, while Labelbox supports many use cases and integrates easily with cloud platforms like Google Cloud, AWS, and Azure. CVAT remains the go-to for developers and research teams looking for a free, customizable tool, but may require more setup and maintenance than SaaS tools. Lightly specializes in self-supervised learning and dataset curation, prioritizing complex examples using embeddings. Label Studio is popular among technical teams for its flexibility and open-source extensibility, while Basic.ai offers a combined platform and workforce solution, supporting Lidar, image, and video data. The ideal tool depends on team size, data type, and regulatory needs, with Encord leading as the most complete, scalable, and secure solution for high-stakes data applications.