Learn how to label your data and train your AI models 10x faster while improving data quality and model performance.
See how our platform can be customized to fit your specific use case
Speed up manual labeling by 10x using custom trained models and generative AI
Prevent labeling errors using Inter-Annotator Agreement (IAA) feature
Increase accuracy and speed using active learning
Collaborate with your team and manage labeling tasks effectively with proper quality controls
On-premise or on the cloud, label your data and train your model at the speed of thought with UbiAI Enterprise.
Whether its PDF, Image or text, parse any document with unparalleled accuracy using Optical Character Recognition (OCR) technology
Leverage AI to auto- label your entities, relations and document classifications at scale with just one click
Training state-of-the-art AI model on your annotated dataset with few clicks without any code
Generate an API endpoint of your trained model with just few clicks, it’s that simple
VietnamWorks is a significant player in the online job board industry of Vietnam. It serves as a platform connecting job seekers with potential employers and offers various features to facilitate this process, including job search, job application, resume creation, and career advice …
The Rockefeller Foundation Archive Center is a unique institution that offers much more than just a repository of historical documents and artifacts. It is also a vibrant research facility that has supported many important initiatives in public health, education, arts, and scientific research….
UBIAI offers a free access with limited functionalities to experiment without any payment required. Anytime during or after the trial, you have the option to upgrade to any of our packages.
Yes, UBIAI is one of the few annotation tools that provide the option to pay for what you use without any additional cost.
Yes, UBIAI supports over 20 languages including French, Spanish, Arabic, Chinese, Russian, etc… for OCR and non-OCR documents.
Yes, UBIAI supports annotation import by uploading a JSON or IOB format that contains the text and labels.