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Lokesh Harjani, CEO & Founder, Onspot Solutions is involved in developing Cloud-based authentication and other anti-counterfeiting solutions. Here he talks about this segment to us.
What techs are involved in anti-counterfeiting and product authentication?
Lokesh Harjani - The product authentication and anti-counterfeiting system work with existing barcodes and packaging with potential small adjustments or add-ons using QR codes and other forms of overt and covert tracking measures depending on the level of tracking required. It eliminates the need to make many changes to the way a brand is currently protected. The technology is based on a simple smartphone app that allows for product verification and in any location along the supply chain. It also offers a flexible system that allows for individual customization and security upgrades in response to the threat posed by counterfeiters.
Also, a multi-tiered method technology is used at the first level of security; there are elementary, overt elements such as holographic technology and specialised tamper proof labels or in some cases RFID or other tracking beacons. There is a lot of highly sophisticated technology accessible at the next level, namely in the domain of covert security features, such as nano-sized taggants, or invisible inks tied into specific filters in the technology.
The technologies that are a part of the solution are - Ruby on Rails is used to power the back end, which not only has the engine that generates the unique random codes, but also the back end for the client interface, a robust REST API that ensures the data transfer between the Cloud Back End and the Mobile App. Furthermore, a Native Mobile App that scans the codes and sends and receives data back from the Server.
What's the percentage of accuracy of this technology?
Lokesh Harjani - The solutions are 100% accurate. All the codes generated are unique and random, so even if a counterfeiter does access any code, they cannot predict the following code in the batch. Thus, the difficulty of predicting and recreating the codes across the batch makes it difficult for the counterfeiter to create duplicate codes for the entire batch. If multiple scans are coming for the same code from different devices, these get flagged as suspected scans, and their count is maintained in a report.
How has been the reception of this tech in the Indian market in 2020-21?
Lokesh Harjani - In 2020, the global pandemic and the rise of E-commerce sales led to an increase in fake goods. For example, in cosmetics and personal care, there are reports of a 56% increase in counterfeit products sold via online channels. More seriously, fears over shortages of medicines, pharmaceuticals – and now vaccines – in many regions have led to greater penetration of counterfeit goods, against which consumers need protection. This increases the use of anti-counterfeiting solutions; track and trace schemes among brands. In our case, we have welcomed clients across industries on board—clients such as Gulf Oil, Sanofi, Laser India, Halonix Technologies, K-18 (International Hair Products) recently joined hands with us to devise personalised tech solutions. We are finding that market leaders in most segments are adopting this technology.
What are the challenges of running this tech from the Cloud?
Lokesh Harjani - The challenges are that the Cloud back end needs to be integrated at the brand's production line to ensure that these unique random codes are printed on the products before they are dispatched. At the same time, we have also developed a packing software that allows the client to pack and ship these unique codes from their manufacturing lines to the retailer, who interacts with the end customer.
Across the entire distribution chain, scans are done at all checkpoints to ensure that what was sent is received, thus providing a blockchain kind of security until the end consumer receives it. AI is the next measure being undertaken which will add a learning feature, where the software will look for how a counterfeiter works and bridge the gaps accordingly.