Vyz AI

AI-powered image-processing application for large slab analysis, precision measurement, and visual refinement
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Vyz AI is a cross-platform application that transforms how stone and marble fabricators analyse and measure large slabs. Built for iOS, Android, and web, it combines AI-driven image processing with mathematical precision to deliver clean slab visuals and measurements accurate to 1.5 mm, giving fabricators the data they need to cut with confidence and reduce material waste.

AI-Powered Slab Image Enhancement & Pattern Reconstruction
The application processes raw slab photographs through AI models that correct colour, remove glare from polished stone surfaces, and eliminate shadows caused by uneven lighting. Where glare or shadow has obscured surface detail, the AI reconstructs the slab's veining and patterning. The output is a clean, true-to-life representation ready for client review, digital cataloguing, or fabrication planning.
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Precision Slab Measurement (1.5 mm Accuracy)
Using four square markers of known dimensions placed on the slab, the application calibrates the image and calculates real-world distances between any two user-selected points. Measurements are accurate to 1.5 mm, giving fabricators the confidence to plan cuts directly from the app without additional measuring equipment.
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In-App Camera Configuration
In-App Camera Configuration The application connects directly to a camera microcontroller, allowing operators to adjust camera parameters: exposure, white balance, focus, and other settings, without leaving the app. This ensures each capture is optimised before processing, reducing the need for post-capture correction and speeding up the overall workflow.
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The challenge

Large-format marble and natural stone slabs are high-value materials. A single slab can cost thousands of euros, and a measurement error of even a few millimetres during cutting can mean wasted material, mismatched patterns, or costly rework. Fabricators need precise point-to-point measurements across slab surfaces to plan their cuts, but getting those measurements from raw photographs is unreliable.


The images themselves introduce problems. Slabs are typically photographed in warehouses or workshops where lighting conditions vary. Glare from polished surfaces, shadows cast by overhead fixtures, and inconsistent colour reproduction all distort the visual record. Fabricators end up working with images that don't accurately represent the stone's true colour, veining, or pattern, making it harder to match pieces across a project or communicate with clients about material selection.


Vyz AI, a machine vision technology company specialising in Spatial Phase Imaging, needed a purpose-built application that could solve both problems in a single workflow: correct the visual quality of slab images through AI and enable highly accurate measurements directly from those images, all accessible from mobile devices on the warehouse floor.


The solution

Wolfpack Digital designed and developed a cross-platform application, available on iOS, Android, and web, that combines AI-powered image enhancement with precision measurement tools built specifically for large slab analysis.


The image-processing pipeline uses trained AI models to reconstruct slab surfaces from raw photographs. The system detects and removes glare reflections and shadows introduced by the capture environment, then applies intelligent colour correction to produce a clean, consistent representation of each slab. The result is an image that faithfully reflects the stone's natural colour, veining, and surface detail, suitable for client presentations, digital catalogues, and fabrication planning.


For measurement, Wolfpack Digital implemented a mathematical calibration system based on four square markers of known dimensions placed on the slab surface. Using these reference points, the application calculates real-world distances between any two points on the slab with an accuracy of up to 1.5 mm. This gives fabricators a reliable tool for planning cuts, verifying dimensions, and reducing material waste without needing dedicated measurement hardware on-site.


The application also integrates directly with camera microcontrollers, allowing operators to configure camera parameters, such as exposure, white balance, and focus, from within the app itself. This closes the loop between capture and analysis, ensuring that images are optimised at the source before AI processing begins.