V7 Darwin
V7 Darwin is a powerful AI-driven platform for labeling and training data that streamlines the process of annotating images, videos, and other data types. By using AI-assisted tools, V7 Darwin enables faster, more accurate labeling for a variety of use cases such as machine learning model training, object detection, and medical imaging. The platform supports multiple types of annotations, including keypoints, bounding boxes, and segmentation masks. It integrates with various workflows through APIs, SDKs, and custom integrations, making it an ideal solution for businesses seeking high-quality data for their AI projects.
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PostDICOM
PostDICOM is a cloud-based, zero-footprint DICOM viewer and medical image management solution that allows users to view, store, and share DICOM files easily through any modern web browser. It supports a wide variety of modalities including CT, MRI, ultrasound, PET, and X-ray, and enables users to access studies from anywhere without the need for additional software installations. PostDICOM includes robust features such as 2D and 3D image viewing, MPR (multiplanar reconstruction), and image fusion. Users can annotate images, take measurements, adjust brightness/contrast, and apply window leveling. It also offers a teaching file management system for educational purposes, enabling users to create and manage teaching cases. With PostDICOM, medical professionals can collaborate through shared workspaces and control access permissions for other users. It includes tools for patient data anonymization and complies with HIPAA standards to ensure data security and privacy.
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Ango Hub
Ango Hub is a quality-focused, enterprise-ready data annotation platform for AI teams, available on cloud and on-premise. It supports computer vision, medical imaging, NLP, audio, video, and 3D point cloud annotation, powering use cases from autonomous driving and robotics to healthcare AI.
Built for AI fine-tuning, RLHF, LLM evaluation, and human-in-the-loop workflows, Ango Hub boosts throughput with automation, model-assisted pre-labeling, and customizable QA while maintaining accuracy. Features include centralized instructions, review pipelines, issue tracking, and consensus across up to 30 annotators. With nearly twenty labeling tools—such as rotated bounding boxes, label relations, nested conditional questions, and table-based labeling—it supports both simple and complex projects. It also enables annotation pipelines for chain-of-thought reasoning and next-gen LLM training and enterprise-grade security with HIPAA compliance, SOC 2 certification, and role-based access controls.
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Caption Health
Our AI technology enables healthcare providers to perform high-quality ultrasound exams wherever and whenever patients need them, regardless of their familiarity with ultrasound. Ultrasound is a safe, highly effective diagnostic tool, but it can be difficult to master, takes years of specialized training to learn, and image quality can vary. Performing the exam involves unnatural hand-eye coordination and unintuitive visuals. Traditional ultrasound software doesn’t provide instruction on how to move the ultrasound transducer to capture an image, or any real-time feedback on the quality of images being captured. Poor quality images lead to missed opportunities, misdiagnosis, repeat studies, and inconsistent interpretation. As a result, the true value and benefits of ultrasound have not been fully realized. Now, with our technology, any healthcare professional can capture diagnostic-quality ultrasound images thanks to AI guiding them through every step of the scanning process.
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