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V7

An AI Data Engine for computer vision and generative AI.

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What is V7?

V7 is a data platform designed to help teams build and manage computer vision and generative AI projects. It provides tools for labeling images and documents, organising training datasets, and connecting AI models into production workflows. The platform is built for machine learning engineers, data scientists, and teams who need to prepare large volumes of visual data for AI training. V7 handles the practical side of AI development: turning raw images, videos, and documents into properly labelled datasets that models can learn from. It scales from small experiments to enterprise deployments, and includes options for both automated labelling and human-powered annotation services.

Key features

Image and video annotation

Label objects, segments, and classifications across images and video frames

Document processing

Extract and understand information from PDFs and scanned documents with high accuracy

Dataset management

Organise, version, and track training data in a centralised workspace

Workflow automation

Route data through labelling pipelines and connect to AI models automatically

Model integration

Plug trained models back into your data pipeline to reduce manual labelling work

Professional labelling services

Access on-demand human annotators when you need additional capacity

Pros & cons

Advantages

  • Saves time on data preparation, which typically accounts for a large portion of AI project timelines
  • Supports multiple data types (images, videos, documents) in one platform rather than juggling separate tools
  • Includes both automated and human labelling options, giving flexibility based on accuracy needs and budget
  • Scales from individual projects to large enterprise deployments without requiring platform changes

Limitations

  • Learning curve for setting up complex workflows; simpler projects are more straightforward than highly customised ones
  • Pricing details for higher tiers are not publicly listed, so enterprise costs require direct contact with sales
  • Quality of professional labelling services depends on clear specification of annotation requirements

Use cases

Training computer vision models for object detection, classification, or segmentation tasks

Processing invoices, receipts, or forms at scale for document understanding AI

Building datasets for autonomous vehicle or robotics projects

Preparing training data for generative AI models that work with images

Managing annotation workflows across distributed teams or external contractors

Ready to try V7?

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Pricing

Free

Free

Limited project creation, basic image annotation tools, up to a set number of images

Pro

Contact for pricing

Unlimited projects, advanced annotation tools, dataset management, workflow automation, API access

Enterprise

Contact for pricing

Custom features, dedicated support, professional labelling services, advanced security and compliance options

Get started with V7

Click through to V7 and start using it now.

Try V7 free
  • Free plan available
  • No credit card