Where Vision AI Learns

Label Training Data at Unsupervised Speed

A class agnostic, pixel perfect automated annotation platform. Built for teams with lots of data, strict quality requirements, and little time. Scale your ground truth creation 10x, collaborate with unlimited team members and annotators, and seamlessly integrate it into your deep learning pipeline. V7 Darwin supports medical and scientific imaging, and video.

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Harness the Sense of Sight

If AI is truly intelligent, it should not be complex to train.

Label, organize, and launch your computer vision products from a graphical user interface, with zero compromises to AI accuracy.
Within a single no-lock-in ecosystem, leverage the smoothest dataset management experience, the most accurate automated annotation, and the ability to train and maintain state of the art models that continually learn from your data.

We are turning advanced vision AI development into a graphical, integration-friendly software experience accessible to businesses large and small. Take a look at some common examples where V7 is used to deliver end-to-end vision:

life sciences AI

Life Sciences

Microscopy

Cells, microorganisms, clusters, in bright and dark microscopy
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Pipetting

Liquid levels and impurities
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Manufacturing computer vision

Manufacturing

Defect Inspection

Small and uncommon defects
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Materials Science

Rust, wear, and materials analysis
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Protocol Logging

Assembly step sequence understanding
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Agri Tech computer vision

Environmental

Plant & Field Agriculture

Plant growth and yield
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Livestock & Wildlife

Livestock and wildlife health
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Get Inspired

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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Ready to get started?

Schedule a demo with our team or discuss your project.