OCI Data Labeling

High-quality training data is essential for all large language models, whether you build the data yourself or use pre-existing models. A human-in-the-loop labeling process delivers real-time feedback for fine-tuning datasets to build the most performant and differentiated AI models. We provide precise data labeling with faster human input to enhance the robustness and input diversity to improve the adaptability of LLMs for your enterprise applications. Our labeler management allows us to segment teams— you only pay for the level of experience and skill sets your data labelling project requires. Sapien can quickly scale labelling operations up and down for annotation projects large and small. Human intelligence at scale. We can customize labeling models to handle your specific data types, formats, and annotation requirements.

Datature is a comprehensive, end-to-end, no-code computer vision and MLOps platform that simplifies the entire deep-learning lifecycle by letting users manage data, annotate images and videos, train models, evaluate performance, and deploy AI vision solutions, all within one unified environment without coding. Its intuitive visual interface and workflow tools guide you through dataset onboarding and annotation (including bounding boxes, segmentation, and advanced labeling), let you build automated training pipelines, monitor model training, and assess model accuracy with rich performance analytics, and then deploy models via API or for edge use so trained models can be used in real-world applications. Designed to democratize access to AI vision, Datature accelerates project timelines by reducing manual coding and debugging, supports collaboration across teams, and accommodates tasks like object detection, classification, semantic segmentation, and video analysis.