AI, digital readers and software for rapid diagnostics

Desktop and smartphone readers turn a visual line into an objective, recorded result, and can open the door to semi-quantitative or quantitative claims. We configure the assay, cassette and reader together, and plan for calibration, lot-to-lot consistency and the data your users need.

Machine learning can read results consistently across lighting conditions, phones and users, and flag invalid tests before they cause harm. Its value depends on training data that reflects real-world use. We help define image capture, reference methods and the validation studies that show the model performs as intended, along with how performance will be monitored once the product is on the market.

If your app or algorithm interprets results, guides clinical decisions or connects to patient records, it may be regulated as a medical device in its own right. Classification decides the evidence, documentation and QMS you will need, so it pays to define this early. Together with Abingdon AI & MedTech, we support qualification and classification, IEC 62304 software lifecycle, ISO 14971 risk management and submissions in the US, EU and UK.

Connected tests can feed results into electronic records, surveillance programmes and clinical trial datasets. They also generate real-world performance data that strengthens post-market surveillance and supports future claims. We help you decide what to capture, with patient safety, data protection and cyber security considered early rather than retrofitted.