Description
V7 is an AI data engine tailored for computer vision and generative AI. It serves as an infrastructure for enterprise training data, providing features such as labeling, workflows, datasets, and human-in-the-loop training.
It provides various annotation options that help to improve the quality of data intended for AI models. The platform automates and streamlines tasks with capabilities like automated annotation, DICOM annotation for medical imaging, dataset management, and model management.
The image and video annotation tools enhance the accuracy of data labeling. It also supports the development and automation of tailored data pipelines and includes tools that automate optical character recognition (OCR) and intelligent document processing (IDP) processes. V7 enables users to delegate annotation tasks to external resources.
It's applicable across diverse industries like agriculture, automotive, construction, energy, food and beverage, healthcare, and more. It offers collaboration tools for real-time team annotation and provides analytics on labeler and model performance. Furthermore, V7 streamlines annotation and model training workflows with an intuitive user interface.
It boosts annotation speed and accuracy through its enhanced AutoAnnotate feature. The platform integrates with services like AWS, Databricks, and Voxel51, and supports multiple data formats including video, images, and text.
Pricing Plans
Releases
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Pros & Cons
Pros
Infrastructure for training data at the enterprise level
Feature for training involving human input
Numerous properties for annotation
Cons
No support for on-premise deployment
Limited options for integration
Only compliant with SOC2, HIPAA, and ISO27001
