Best Video Annotation Tools for Azure Blob Storage

Compare the Top Video Annotation Tools that integrate with Azure Blob Storage as of October 2025

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This a list of Video Annotation tools that integrate with Azure Blob Storage. Use the filters on the left to add additional filters for products that have integrations with Azure Blob Storage. View the products that work with Azure Blob Storage in the table below.

What are Video Annotation Tools for Azure Blob Storage?

Video annotation tools are computer-assisted programs designed to help organize and analyze video data. Most tools are designed for use with machine learning, allowing users to create labels, tags, and other forms of metadata that can be used to train AI models. Annotations can also be used to assist with traditional tasks such as tracking the progress of actors within a scene or counting the number of objects in an image. These applications allow for efficient analysis of large amounts of video data without manual effort. Compare and read user reviews of the best Video Annotation tools for Azure Blob Storage currently available using the table below. This list is updated regularly.

1

Ango Hub

iMerit

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.

15 Ratings

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2

V7 Darwin

V7

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.

Starting Price: $150

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3

CVAT

CVAT

Annotate better with CVAT, the industry-leading data engine for machine learning. Used and trusted by teams at any scale, for data of any scale. CVAT’s blazing-fast, intuitive user interface, was designed by working closely with real-world teams solving real-world problems. From medical to retail to autonomous vehicles, world’s most ambitious AI teams use CVAT as a part of their AI workflow every day. No matter what your input data or expected results are, CVAT is ready. It works great with images, videos, and even 3D. Bounding boxes, polygons, points, skeletons, cuboids, trajectories, and more. Annotate more efficiently with automated interactive algorithms like intelligent scissors, histogram equalization, and more. Gain actionable insights with metrics such as annotator working hours, objects per hour, and more.

Starting Price: $33 per month

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4

Label Studio

Label Studio

The most flexible data annotation tool. Quickly installable. Build custom UIs or use pre-built labeling templates. Configurable layouts and templates adapt to your dataset and workflow. Detect objects on images, boxes, polygons, circular, and key points supported. Partition the image into multiple segments. Use ML models to pre-label and optimize the process. Webhooks, Python SDK, and API allow you to authenticate, create projects, import tasks, manage model predictions, and more. Save time by using predictions to assist your labeling process with ML backend integration. Connect to cloud object storage and label data there directly with S3 and GCP. Prepare and manage your dataset in our Data Manager using advanced filters. Support multiple projects, use cases, and data types in one platform. Start typing in the config, and you can quickly preview the labeling interface. At the bottom of the page, you have live serialization updates of what Label Studio expects as an input.

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