If you're looking for a V7 alternative, Encord is another top option. This platform provides a full-stack data development environment for training and deploying computer vision models, both predictive and generative. It includes data ingestion, cleaning, curation, automated labeling and model performance evaluation tools. Encord is easy to use and accommodates a range of annotation formats, which is why it's a good choice for teams that want to accelerate their AI development workflows.
Another option is Clarifai, which takes a different approach by focusing on AI workflow orchestration. It makes it easier to build and run AI projects with automated data labeling, generative AI and content moderation. Clarifai is geared to help you move AI prototypes into production more quickly, cutting development costs and speeding up work, so it's a good choice if you want to operationalize AI for many use cases.
If you're looking for a platform that can handle training and deployment of AI models, SuperAnnotate is another option. It can handle a lot of data types and can pull data from local and cloud storage systems. The platform has built-in AI, QA and project management tools, as well as a global marketplace for annotation teams. That makes it a good choice if you want to ensure high-quality training data and model performance while meeting data security and privacy requirements.
Last, Label Studio is a flexible data labeling tool that can handle images, audio, text and video data. It's got customizable layouts and templates, ML-assisted labeling and integration with cloud storage systems. Label Studio is open-source and free, but it's also got an enterprise version with more features, so it's good for small teams and large enterprises.