Build Robust Vision AI

The Most Powerful Platform for Image Recognition

V7 develops the most comprehensive toolkit for managing datasets, annotating images, training models, and deploying them in production from the same source. You won't have to leave your browser or work your way through compatibilities. V7's technology is built with medical and scientific usage compatibilities, including regulatory compliant annotation and format supports.


Data become an organized, collaboratively usable resource on the fastest dataset management platform for machine learning.

Butter smooth browsing

We are serious about presenting your data with no loading times. Uploads, filters, and search queries will always be delivered in real-time, no matter how large your dataset.

Format friendly

DICOM, .TIF, .MOV, or other uncommon formats are welcome! From electron microscopes to 4k cameras, most image data will work on V7.

Annotate, train, export, collaborate, and share

Datasets are at the core of your AI projects - use them to train networks, iterate new versions to improve performance, grow them with your team, or share them with the wider community.


V7 was built in Elixir, an Erlang-based language to handle massive scale concurrency between millions of users moving billions of images.
Whether you are uploading, exporting, annotating, or partitioning, your data will always be swiftly available.

"We use this thing every day, it's like, really great. Our data is very important to us."


Tell your AI what to learn. Annotate yourself or hire a team through V7 - your datasets will be annotated and ready for training.


Save up to 80% of your annotation time while matching human performance. V7's Auto-Annotate tool works on any object, big, small, partial, or compound. Try it to believe.

Quality Review

Annotation follows a pipeline where images are marked for review before they are complete. Reviewers can comment on errors and assess each image.

Outsource or BYO

Upload your data and let us take care annotations through experienced annotators. You can track its progress and quality and train models on it as it grows.
If you have your own team of annotators, you can add them all, for free, with no limitations.

Expandable Tools

Tags, bounding boxes, polygons, masks, directional vectors, attributes are available from the get-go.
V7's toolkit keeps expanding, and if you need something special you can add new annotation types and tools as plugins.

"Wow, annotation is rad."


One click is all you need.
Welcome to the future of training deep neural networks.


One of our goals at V7 is to automate our own jobs as machine learning scientists. Our platform will select the right hyper-parameters, augmentation flow, data splits, and more to give you the same value as a small team of deep learning engineers.

Your Model Library

We know the pain of logging each trained model's stats. V7 does that for you, generating performance metrics, confusion matrices, and allowing you to view the test images where your model performs well or badly.

It's Better

The user experience of training models isn't something most people think about. We do.
Get notified when your models are ready, share their performance, and never look back at your old ways.

Your place or ours

Load the right dataset version with a single command into your cluster, or immediately start training in the cloud through a user-friendly GUI.

Compatibility troubleshooting is a thing of the past, claim those hours of your life back.

"Wow, annotation is rad."


The most powerful artificial minds created by humankind so far, seamlessly running through your browser or app.

3, 2, 1, Go

It just works - Once your models are trained you can run them directly through your computer's webcam.


Once your models are running, you can obtain rich, live data on what they recognize.


Test your model, or continue running it on V7's iOS app.
You will have a portable AI camera to demo your new model with no additional work.

Launch your Product

V7 is here to support your AI-enabled product's success. Once your neural networks are running you can integrate them into your products. If they need to run locally, get in touch and we will help.

"Wow, annotation is rad."

Create the Sense of Sight

Explore some of the applications you can develop on V7. Harness AI to turn industries and products into sighted, intelligent systems.

Develop a compliant cancer decision support system

Add oncologists to your team and minimally involve them in the annotation workflow to develop FDA compliant cancer-detecting AI. Once the expert's input is added, use of V7's annotation network to complete pixel-perfect annotations of medical images.

Detect multiple imperfections in real-time for manufacturing quality control

Label imperfections in images and train a robust neural network with Auto-Train. Test it on the production line through a webcam or iOS device and later deploy it on a server to match your production line speeds.

Recognize and track objects in a chemical laboratory

Develop an object detection for items you work with to automatically document their involvement in protocols. Use V7 to understand object presence, orientation, and components.

Analyze and count cells in microscopy images

Load microscopy images into V7 and use Auto-Annotate to quickly create a segmentation dataset of cells and organelles, then train a neural network to instantly detect cell count, shape, and appearance.

Detect Macular Degeneration in Ophthalmological Images to Prevent Blindness

Segment capillaries and retinal spots with Auto-Annotate, then train a robust semantic segmentation model to obtain a mask of the eye's capillaries and a detector for retinal spots. Combine the two to diagnose AMD and diabetic retinopathy, the leading causes of blindness.

Develop your next game changing idea

Use V7 to give the sense of sight to any device or service. Neural networks are trained to learn the data you feed them, meaning you can develop an AI for any scenario that can be captured in images or video.

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Technology Ecosystem

V7 guides you through the creation of your machine learning product with a connected ecosystem of tools. You can make use of one, or all of them as you see fit for your project.

Diagram of V7 Darwin

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