If you're looking for a UBIAI alternative, SuperAnnotate is definitely worth a look. This platform is geared for training, testing and deploying high-quality LLM, CV and NLP models using high-quality training data. It can pull data from local and cloud storage systems and offers a customizable interface to accommodate a broad range of GenAI use cases. SuperAnnotate also offers advanced AI, QA and project management tools, making it a good choice for those who want to automate their AI development workflow while maintaining data security and privacy.
Another good option is Encord. This full-stack data development platform is geared for building predictive and generative computer vision applications. Encord offers different types of annotation and automated labeling, as well as monitoring and testing model performance. It's designed to be secure, with certifications like SOC2, HIPAA and GDPR, and offers different pricing tiers for different needs. The platform's ease of use and support infrastructure can help you accelerate AI development lifecycles while keeping training data high quality.
V7 is another option. V7 is a machine learning development platform that focuses on optimizing data labeling and automating tasks to reduce costs and accelerate project delivery. It offers tools like V7 Darwin for image and video labeling and V7 Go for multi-modal tasks. With its SOC2, HIPAA and FDA compliance, V7 is geared for different industries, and it offers multiple pricing tiers for different business needs.
Last but not least, Label Studio is a flexible data labeling tool that can handle images, audio, text, time series and video data. It offers customizable layouts and templates, ML-assisted labeling and integration with cloud storage systems. With its open-source nature and free version, Label Studio is available to small teams and data scientists, and it's a good option for creating high-quality training data for a wide range of AI applications.