GC-MS automation for SVHC detection

A global testing provider selected Virtual Control to improve accuracy, reduce variability and lower cost in performing of Gas Chromatography Mass Spectrometry (GC-MS) analysis.

By using custom Machine Learning algorithms, the solution reduced PhD chemist effort by over 70%‎

Phthalates detection

Phthalates are added to plastics to increase their flexibility, transparency, durability, and longevity but can be hazardous.

Virtual Control are in early Proof of Concept examination utilizing custom Machine Learning algorithms, to remotely detect and identify peaks in Phthalate volumes in samples for test laboratories

Formaldehyde detection

A global testing provider selected Virtual Control to detect formaldehyde and other select hazardous chemicals without the need for extensive, specialist analysis.

By using custom Machine Learning algorithms, the solution reduced PhD chemist effort by over 25%‎

Semi-Conductor Chip Analytics

To detect fraudulent and grey market semi conductor chips, our client needed assistance in quickly and cheaply inspecting chip design, label, logo positioning and watermark detection.

Based on a small sample, Virtual Control demonstrated the ability identify at risk items with over 92% accuracy

Green Compliance

Stringent European Standards for energy compliance and labelling can be a trigger to customs fines and product recalls.

Based on Virtual Control’s Computer Vision and Machine Learning solution, the client was able to automatically inspect electronic devices to identify that label standards were met at point of manufacture.

Label Compliance

A global pharmaceutical leader must comply with local jurisdictions for labeling of high value medical products.

The current manual process requires duplicate handling points, re-typing of information across systems and inefficient report generation.

We look to automate E2E the batch label inspection and report generation process.