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Computer vision platform for building and deploying AI models with automated annotation tools.
Roboflow is a comprehensive computer vision platform that provides everything developers and enterprises need to build, train, and deploy computer vision models. The platform addresses the complete machine learning pipeline from data collection and annotation to model training and deployment, making computer vision development accessible and efficient.
Core Capabilities: Roboflow offers an integrated suite of tools including Universe (open source datasets and pre-trained models), Annotate (AI-assisted data labeling), Train (hosted model training with GPU access), Workflows (low-code pipeline builder), and Deploy (multi-environment deployment options). The platform supports various computer vision tasks like object detection, classification, segmentation, and tracking.
Key Features: The platform provides AI-assisted annotation tools that can accelerate labeling by up to 10x, automated data augmentation to generate up to 50 variations per image, and hosted training infrastructure optimized for computer vision workloads. Users can deploy models via API, edge devices, or in their own VPC, with comprehensive monitoring and analytics.
Value Proposition: Roboflow eliminates the complexity of computer vision development by providing an end-to-end solution that reduces development time from months to weeks. The platform's integrated workflow ensures that what can be configured can be deployed, while the extensive dataset library and pre-trained models accelerate development.
Target Users: The platform serves over 1 million engineers and 16,000 organizations, including half of the Fortune 100. It's designed for machine learning engineers, data scientists, developers, and enterprises across industries like automotive, healthcare, retail, manufacturing, and aerospace who need to implement computer vision solutions.
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Pricing Model
Supported Platforms
Supported Languages
Label images up to 10x faster with automated annotation tools and collaborative workflows.
Train models on optimized infrastructure with GPU access and five model size options.
Build computer vision pipelines combining custom models, APIs, and logic without coding.
Deploy via API, edge devices, or VPC with comprehensive monitoring and metrics.
Access thousands of open source datasets and pre-trained models to jumpstart projects.
Generate up to 50 augmented versions per image to improve model generalization.
