Where Vision AI Learns

COVID-19 - Business continues as usual. We are  working on annotating open datasets and dedicating resources to develop models for COVID-19 research. More news coming soon. Enquire to collaborate.

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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You are in good company

Give Machines the Sense of Sight

V7 Neurons are specialized AI modules that excel in their domain, and can be easily re-trained on new objects to fit your project. Neurons reduce the development time of an AI project from months to days, with V7's guarantee of state-of-the-art performance.

Neurons are a combination of neural network architectures, annotation schemas, augmentations, training pipelines, and other parameters continually tested to work best in their visual scenario.

life sciences AI

Life Sciences

Cellularis

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

Liquid levels and impurities
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Manufacturing computer vision

Industrial

Meticula

Small and uncommon defects
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Vulcan

Rust, wear, and materials analysis
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Maestro

Human-object interaction
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Agri Tech computer vision

Environmental

Ivy

Plant growth and yield
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Artemis

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.