Though custom-built solutions are creating lasting change in various IIoT-involved fields, it’s still not uncommon in warehouse environments, as an example, for teams to be left with the task of double-checking and triple-checking barcode scanning tasks in order to combat low accuracy with cycle counting. These counts may only partially represent inventory, to boot; capacity constraints can make it increasingly difficult for workers to survey a full warehouse. Studies have shown that, on average, inaccurate inventorying can cost a business hundreds of thousands per year (and per warehouse), plus significant revenue loss due to missed orders.
Gather AI is doing something about this problem.
Gather AI automates inventory visibility challenges through easy-to-operate autonomous drones across third-party logistics, manufacturing and retail facilities, with much richer data than warehouses can typically obtain with barcodes. Gather AI has since established successful relationships with customers like NFI, GEODIS, DSV, Barrett Distribution, and DPI Specialty Foods (KeHE), and the locations it serves become bona fide cutting-edge warehouses with drone-powered inventory monitoring, as a result. Gather AI’s drones improve warehouse productivity by decreasing the cost of inventory accuracy while decreasing shrinkage, and they improve overall on-time fulfillment.
So how do Gather AI’s drones work? Well, a user can start by picking the area of a warehouse that needs to be scanned. Then, they’ll take the drone and accessories to that area. Via the iPad app, it’s as simple as selecting the desired bins for scanning, then placing the drone on the ground and pressing “Take Off” to watch it fly autonomously as it takes photos of the selected bins. The drones rely on labels placed on warehouse racks to navigate efficiently, and they’re built to fly in most warehouse spaces with zero modifications required.
“You no longer need scissor lift or other inventory equipment, as the drones go high up in the racking,” one Gather AI representative stated. “They fly without Wi-Fi, work in the dark and in coolers, and operate well even in incredibly narrow aisles.”
The drones land when they’re done collecting data or batteries are low; in the latter’s case, just swap the battery and re-launch to continue the mission. These drones are capable of scanning upwards of 300 pallets per hour, and additional drones can be launched and controlled simultaneously, as well. (“Even 900 pallets per hour,” some Gather AI partners have noted.)
After a mission is complete, images are automatically uploaded to the cloud for processing and displayed in the dashboard (with the organizational assistance of Gather AI’s machine learning algorithms). Using the dashboard to view inventory matches, empty bins and missing LPNs, floor visit rates can be reduced and warehouse utilization becomes as achievable as it is optimizable.
And in related news, Gather AI recently announced its $17 million Series A-1 funding led by Bain Capital Ventures (with participation from Tribeca Venture Partners, Dundee Venture Capital, Expa Ventures, and Bling Capital). The new funding provides a total of $34 million raised to date, which is actively being invested in scaling operations as Gather AI continues resolving businesses’ supply chain issues.
“Gather AI’s cutting-edge computer vision and workflow software, purpose-built for inventory monitoring, has seen significant commercial adoption and rapid growth separating them from the field of other venture-backed startups,” said Ajay Agarwal, partner at Bain Capital Ventures. “We are excited to welcome Gather AI to our portfolio of companies such as Kiva, ShipBob, FourKites, and Vention that are leveraging AI and software in the physical world.”
“We’re already seeing the positive impact of Gather AI on customers spanning third-party logistics, retail, food and beverage, and manufacturing,” said Sankalp Arora, co-founder and CEO of Gather AI. “AI-powered cameras will transform supply-chain traceability to have a similar impact that barcodes did in the 1980s, and our technology is at the forefront of this transformation.”
Edited by
Greg Tavarez
