V7Labs

AI data engine for computer vision and generative AI

Data labeling· 4.5·0 saves·Freemium

Quick facts

Best for
Data labeling
Pricing
Freemium
Editor rating
4.5 / 5
Community saves
0
V7Labs screenshot 1

About V7Labs

V7 is an AI data engine designed for computer vision and generative AI applications. The platform provides an infrastructure for enterprise training data that includes labeling, workflows, datasets, and has a feature for human-in-the-loop training. It offers multiple annotation properties to improve the quality of data for AI models. With features like auto annotation, DICOM annotation for medical imaging, dataset management, and model management, V7 automates and streamlines various tasks. Its image and video annotation tools are designed to improve the precision of data labelling. Additionally, it enables the building and automation of custom data pipelines and has tools for automating optical character recognition (OCR) and intelligent document processing (IDP) workflows.V7 allows users to outsource annotation tasks. It can be used across various industries such as agriculture, automotive, construction, energy, food & beverage, healthcare, and more. It offers collaboration features for real-time team annotation and provides labeler and model performance analytics.Further, V7 also facilitates annotation and model training workflows to be more efficient through an intuitive user interface. With its enhanced AutoAnnotate feature, it accelerates the speed and accuracy of annotations. The platform integrates with AWS, Databricks, and Voxel51, among others, and supports a range of data types including video, image, and text data.

Pros

  • Enterprise training data infrastructure
  • Human-in-the-loop training feature
  • Numerous annotation properties
  • Auto annotation feature
  • DICOM annotation for medical imaging
  • Dataset management capability
  • Model management feature
  • Optimized for data precision
  • Custom data pipelines automation
  • OCR and IDP workflow automation
  • Outsource annotation tasks feature
  • Cross-industry application

Cons

  • Lacks on-premise deployment
  • Limited integration options
  • SOC2, HIPAA, ISO27001 compliance only
  • Outsourcing tasks not private
  • Vague labeler performance analytics
  • Limited data format support
  • No direct tech support
  • Proprietary Auto-Annotate feature
  • Limited Bounding
  • Box tools

Pricing

Pricing model
Freemium
    Paid options from
    Free tier available
      Billing frequency
      Monthly