Pricing score

V7 Pricing Profile

V7 is a powerful AI training data platform that enables you to annotate images, videos, documents, and medical imaging files. It is the quickest way to obtain high-quality annotated data for training your computer vision models.

HQ Location

London, England

Category:

Key Takeaways

AI-Assisted Labeling

V7 helps data teams reduce labeling time by providing AI-assisted tools that speed up the annotation process.

Data Augmentation

Tools for generating synthetic data through augmentation.

Integration with ML Frameworks

V7 integrates with frameworks like TensorFlow, PyTorch, and YOLO, making it easier to train models with labeled data.

Product Overview

V7 Labs is an AI-powered data annotation and computer vision platform designed to streamline the process of training machine learning models, particularly in the area of computer vision. V7 provides tools for data labeling, model training, and deployment, helping data science teams and companies accelerate their machine learning workflows, especially when working with visual data.

V7 Labs is known for its focus on AI-assisted labeling, making it an essential tool for businesses and teams working with large volumes of visual data who need to quickly and accurately label images for tasks like image classification, object detection, segmentation, and more.

INSIGHTS

Our insights about V7 pricing

Free plan

Custom options

Free trial

Available Pricing Models

How much does V7 cost?

V7 offers Free plan with token credits included, and up to 10 seats.

Self Serve

For small teams looking to automate tasks with foundation models.
The price is $249/month.

Enterprise

For large-scale usage, dedicated integrations, and white-glove workflow build-outs from expert AI engineers.
Pricing available upon request.

What users say about V7 pricing

Derek V.

Spreadsheet tech hasn't really changed since 1979 when VisiCalc was introduced with support for formulae in spreadshset cells. V7 has changed that - having an LLM running inside each cell and allowing cells to contain rich content like handwritten documents or scanned paperwork is a huge game changer!

Kirti P.

Exporting the documents and annotating and labeling them. All its functionalities and excellent and up to our requirements. The arrangement of its UI and tool is so exciting and intuitive for all users. No confusion while selecting the tool for your desired work. Its automotive features are unique, helping you make your job done more efficiently and in less time with more accuracy. Enables you to manage all your teamwork in one place. Supports multiple processes and operations.

Suneth T.

After several tries trying out various tools to annotate my data, I stumbled on V7 and immediately realised that V7 had exactly what I needed. My datasets have a lot of similar images and V7's copy annotations feature helps save a ton of time and allows me to work through my datasets swiftly. Furthermore, I never knew I needed the image manipulation options that V7 provides until I used it. It allowed me to completely isolate my items from the noise for more accurate annotations.

Verified User in Information Technology and Services

It has automatic annotation tool like SAM, and it allows you to merge the polygons, which I find very handy.

ABDUL B.

One of the best things about this tool is its user-friendly data annotation feature. Thanks to the auto-annotation features, I could label my dataset with ease, even for the most complex objects. The tool even allows for the annotation of polygon shapes, which was a massive help for me.

Derek V.

Verified User in Information Technology and Services

It has automatic annotation tool like SAM, and it allows you to merge the polygons, which I find very handy.

Kirti P.

ABDUL B.

Suneth T.

V7 Pricing Rating

Customizable Labeling: 4.8/5

V7 allows teams to create custom labeling workflows tailored to their specific use cases. You can define your own label sets (e.g., object types or categories), shapes (bounding boxes, polygons, masks, etc.), and annotation standards. Whether it's for image classification, object detection, or semantic segmentation, V7 can adapt to various types of annotation tasks.

API and Integration: 4.7/5

V7 offers a RESTful API that enables automated integration with external systems and tools. This allows for a smoother workflow, especially when dealing with continuous data updates or when working with third-party applications. APIs can be used to automate data uploads, fetch annotations, or integrate V7 with existing machine learning pipelines.

Collaborative Annotation: 4.9/5

V7 allows teams to collaborate in real-time on annotation projects. Multiple users can work on the same project, making it easier to manage large datasets and ensure quality control.

FAQ on V7 Pricing

Why should I use Go instead of calling a model provider directly?

Go is more accurate and robust than calling a model provider directly. By breaking down complex tasks into reasoning steps with Index Knowledge, Go enables LLMs to query your data more accurately than an out of the box API call. Combining this with conditional logic, which can route high sensitivity data to a human review, Go builds robustness into your AI powered workflows.

Is V7 Go part of V7 Darwin?

V7 Darwin is a data labeling platform for annotating videos and medical imaging to train your own model, while V7 Go specializes in applying foundation models to multimodal data, starting with intelligent document processing. In time they will be natively connected.

How do the limits of the Self Serve plan work?

The Self Serve plan is limited on fields (what you would call ‘cells’ in a spreadsheet) and Go tokens, which are consumed when you use AI models. The field limit does not refresh, while your token allowance resets on the same cadence as your billing cycle, either monthly of yearly. While both fields and tokens are a hard limit, they can be increased by expanding your plan.

Does V7 Go support external models?

V7 Go will support external models via API, allowing for a flexible approach to document processing by incorporating both in-house and third-party AI models.