In a world susceptible to external shocks, computer vision, artificial intelligence (AI) and machine learning (ML) together provide an answer, enabling workers, customers and businesses to adapt to changing environments. Our technology uses the camera on smartphones, wearables and robots to interact with physical objects to read barcodes, text and images. Blending physical and digital worlds in this way is proving valuable in countless ways, such as medics scanning test samples in field hospitals or for couriers sorting parcels to fulfill soaring e-commerce demands.
Our Smart Data Capture platform and its potential to transform the daily lives of workers, customers and businesses has secured the confidence and backing of investors, led by Warburg Pincus, to the value of $150 million. With this new Series D funding, which makes us Europe’s newest unicorn with a valuation in excess of $1bn, we’re embarking on the next phase of our technology roadmap. The investment further boosts our engineering efforts to make life simpler for workers by making our technology smarter through the use of AI/ML, and ultimately delivering a better customer experience. And, as we enter a new phase, we’ll extend the capabilities of smart data capture beyond smartphones to autonomous devices and unlock new value in our core sectors.
The road ahead
Our technology roadmap is supported by three core pillars of product development: expanding our technology to new devices, smart enablers, and tailoring computer vision for specific vertical solutions.
‘’Scandit’s Smart Data Capture technology is transforming the way businesses operate and interact with their customers in an increasingly digital world and is strongly aligned with some of the biggest secular trends of our time, including enablement of the digital workforce and supply chain visibility.”Flavio Porciani, Managing Director, Warburg Pincus
Advance to autonomous devices and wearables
The drive to bring the benefits of smart data capture that are tried and tested on smartphones to autonomous and wearable devices is already underway. We’ve already had a glimpse of how productivity and profits are boosted by marrying existing infrastructure with the power of smart data capture. A pioneering US customer is using ShelfView, our shelf management solution for retail, on autonomous floor scrubbers to gain visibility of shelves and stock in real time – believed to be the largest production deployment of a robotic based computer vision solution in retail. By processing the captured data in the cloud and providing actionable insights, the retailer can optimize replenishment of shelves, fix incorrect price and promotions and increase the accuracy of order-picking to fulfill its burgeoning e-commerce channel efficiently. The results of this are not insignificant especially in a time of rising labor costs with any one second saved in average order picking time per item translating to up to $10 million of annual cost savings.
Drones and robots are rapidly becoming regulars in the modern factory and warehouse – coupled with computer vision, they’re accurate and efficient at tracking assets. When they’re connected to the cloud they can be paired with other intelligent capabilities to create new business models. The benefits of ShelfView we have seen in retail could start to be applied in such environments to provide greater accuracy in pallet localization and asset management.
Numerous other potential applications can be applied and value unlocked by deploying stationary and autonomous devices in various industry scenarios. Stationary cameras, for example, are a simple yet effective means of monitoring stock in highly regulated or high margin sectors. Medical device and pharmaceutical manufacturers can put stationery cameras in front of shelves to observe inventories, typically worth millions of dollars, gaining an accurate view of assets and removing human error.
Smart enablers — the worker’s friend
Today, MatrixScan captures multiple barcodes simultaneously and beats dedicated scanning devices with performance that’s at least five times faster. Now, fresh funding will let us enrich the functionality of our Smart Data Capture platform further, adding more value and improving the employee experience by taking the toil out of tasks. We’ll do this by deploying AI/ML more to enhance image recognition and detect barcodes and visual objects.
Automating the recovery from mistakes and adding other intelligent activities like counting to our computer vision capability are real game changers in warehouses, the last mile and back of house retail operations. Advancements will flag barcodes that aren’t decoded or may be duplicated, letting a worker manage the problem with minimal sweat. Such smart enablers are moving the burden of scanning or identifying errors from the user to the technology, enabling the employee to become more efficient.
Our engineering efforts will make smart data capture the worker’s new best friend in other ways, providing precision and accuracy while taking the drudge out of manual chores. The capability of detecting and overriding duplicates is valuable in logistics work when it’s difficult to hold a camera-enabled device steadily, perhaps when sorting parcels in a moving van. Similarly, it may be challenging to reliably preview stock that is beyond the view of the camera lens, whether scanning shelving units in warehouses, or on shop floors. In those instances, the technology will be able to counteract unintended human movement and duplicate items erroneously captured during the stock take.
Pairing AI/ML with optical character recognition (OCR) generates another valuable superpower — detecting fraudulent documents with a simple scan. Training AI/ML models on authentic documents enables increased accuracy to detect fake IDs by spotting patterns that don’t match the genuine document. Scaling the identification of fake IDs on a large scale is valuable in many areas such as age-verified delivery or the purchasing of age-restricted goods in retail stores.
Transformation of verticals
Activated by the new funding, a broad set of technology initiatives at Scandit, including the advanced use of machine learning, image processing and text recognition techniques, will ensure even more areas across our core sectors – retail, transportation and logistics, healthcare, and manufacturing – benefit from computer vision. One new innovation we are working on will transform the daily lives of workers across a number of retail tasks by scanning high volumes of barcode at speed without the need to align the barcode and viewfinder. In the transportation and logistics sector, adding an augmented reality overlay to digital eyewear can speed up processes leading to efficiency gains by instructing the user. We have already seen this work to great effect in Japan with Yamato Transport using such technology on smartphones to train inexperienced drivers leading to an increase in truck loading times by 20%.
Computer vision is at the frontier and confluence of technology developments with the pervasiveness of AI, 5G and increased computer processing power giving it a new impetus. Our computer vision heritage is rooted in a seemingly simple task — the ability to recognise and digitally capture a humble barcode, object or text. Teamed with new technology capabilities and connected to the cloud, it gives superpowers that will make enterprises more profitable, efficient and jobs more human.