In Autumn 2021, gliff.ai completed a feasibility study for an anti-counterfeiting imaging artificial intelligence (AI) platform, working in partnership with Durham University and a multinational manufacturer.
gliff.ai has worked closely with a multinational company for over two years to integrate patented fundamental research from Durham University into an effective anti-counterfeiting solution, using smarter, data-based interventions.
This work will help ensure the safety and integrity of the company’s products, as well as help prevent revenue loss and brand damage. Anti-counterfeiting practices are often time consuming, labour intensive and require expert sample or visual analysis. gliff.ai’s smartphone, photo-based platform, however, will more than double the efficiency of counterfeit detection processes by enabling near real-time identification of a counterfeit product on the market combined with valuable geo-location information.
gliff.ai’s innovative Machine Learning Operations (MLOps) software that underpins the technology will unlock the ability for brands to create accurate image training datasets and create their own artificial intelligence. The development is suitable for large companies as well as SMEs to assist their brand protection strategies.
“Our platform enables the proper curation of a ground-truth dataset of images for training Machine Learning systems,” says Chas Nelson, CTO of gliff.ai. “The importance of using good quality data is imperative to building trustworthy AI.”
The project has been co-funded by the UK’s innovation agency, Innovate UK, which provided a grant of £130,000 for the use of data science to address problems relating to anti-counterfeiting.
“Innovate UK’s support for this project has contributed significantly to this development of an AI and image-based anti-counterfeit technique which could be employed by any industrial organisation,” says Bill Shepherd, CEO of gliff.ai. “Thanks to this innovation, an AI application will be able to automatically detect counterfeit products from smartphone photographs, producing data-rich reports on locations and trends of counterfeiting.”
The project built upon the excellent fundamental research conducted at the region’s universities by Prof. Boguslaw Obara (Professor in Image Informatics) of Newcastle University, and Dr Sarah Xiao (Professor in Marketing) and Peter Allen (Associate Professor in Strategic Management) of Durham University Business School.
Around 3% of goods traded worldwide in 2016 were counterfeit, according to the OECD. Counterfeit goods are wide ranging, readily available online, illegal and potentially dangerous. What’s more, the counterfeit goods market negatively affects the revenue and brand reputation of genuine manufacturers. In 2020 alone, counterfeit clothing resulted in 26.3 billion euros of sales losses worldwide.