InViLab develops custom machine‑vision and AI solutions that convert raw image data into actionable insights for industrial quality control, medical diagnostics, environmental monitoring, and heritage conservation. By integrating multi‑modal imaging (visible, infrared, hyperspectral, 3‑D) with deep‑learning and statistical modelling, they deliver modular software tools or turnkey systems that provide real‑time, high‑precision analysis and automated reporting for manufacturers, healthcare providers, and monitoring organisations.
Funding
Funding not disclosed
Founders
Product
Problem
Industries and healthcare providers often rely on manual visual inspection or legacy imaging systems that are limited in speed, accuracy, and adaptability, leading to inconsistent quality control, delayed defect detection, and suboptimal patient outcomes.
Solution
InViLab develops custom machine‑vision and AI algorithms that transform raw image data into actionable insights for a wide range of applications, including industrial quality control, medical diagnostics, environmental monitoring, and heritage conservation. By integrating advanced imaging modalities—such as hyperspectral, infrared, and 3‑D reconstruction—with statistical modelling and deep learning, the group delivers automated, high‑precision analysis pipelines that operate in real time or near‑real time. These solutions are packaged as modular software tools or turnkey systems that can be deployed on existing hardware or on dedicated sensor platforms, enabling partners to scale inspection processes, reduce human error, and accelerate decision‑making.
Target Audience
Primary customers are manufacturers seeking automated quality‑control systems, medical imaging centers requiring AI‑assisted diagnostics, and organizations involved in environmental or infrastructure monitoring that need scalable vision‑based inspection tools.
Features
- Multi‑modal imaging support (visible, infrared, hyperspectral, 3‑D laser scanning) with calibrated sensor fusion
- Deep‑learning models for defect detection, tissue characterization, and material classification, trained on domain‑specific datasets
- Bayesian and Gaussian‑process statistical frameworks that quantify uncertainty and improve robustness of predictions
- Real‑time processing pipelines optimized for edge devices and GPU clusters, with APIs for integration into production lines or clinical workflows
- Automated reporting dashboards that visualize inspection results, trend analyses, and compliance metrics
- Drone‑compatible vision modules for large‑scale environmental surveillance and infrastructure inspection