The Center for Data Innovation spoke with Andrei Danescu, CEO and co-founder of Dexory, a company that uses AI and robotics to help logistics businesses streamline warehouse operations. Danescu discussed how Dexory uses autonomous robots to capture useful data for AI interpretation and visualization to improve forecasting and drive more intelligent decision-making.
Kir Nuthi: Since COVID-19, the global economy has faced ongoing supply chain issues due to lacking labor capacity and restocking problems. How does Dexory automate inventory management to minimize potential supply chain issues?
Andrei Danescu: It’s an interesting question with a number of factors playing in. The pandemic acted as a catalyst for a lot of very swift changes in logistics-based industries. With the population not leaving their homes very often, consumers turned to online shopping to get the goods they needed, and many never looked back. This caused a lot of problems for logistics businesses as they needed to accelerate quickly without much warning, while much of the industry up to that point had been rooted in manual processes.
Moving quickly to automation was one solution, and one that we have seen a rise in the following years. Autonomous robots and machine learning technologies can transform those processes, making them more efficient and safe. The labor gap we’ve been seeing recently is another factor affecting the supply chain and one that these automating systems can help shrink.
Nuthi: Robots-as-a-service integrates an external robotic device into a cloud computing environment. Why did Dexory choose to be a robot-as-a-service versus just a software service?
Danescu: Part of the reason is that Dexory is a full-stack solution provider. We design and build bespoke systems—i.e., the robots—and also create the software to gather and make the data they’re collecting accessible and useful. We found that if we tried other ways—i.e., outsourcing the data collection to the companies once we sold them a robot—it would lead to more issues with software collection, fixing bugs, etc., eventually leading to vastly inferior performance and low customer satisfaction. This way, we can help make sure everything’s running smoothly, and updates to the fleet or providing new models are handled by us as leaders in our field. We’ve found that robots-as-a-service is also beneficial to many companies who don’t want to pay a large up-front sum when bringing in automation.
Nuthi: How does Dexory aim to create zero-error warehousing operations globally?
Danescu: This is the holy grail for anyone working in logistics or operations, and we’re no different. It’s really difficult for global companies to have a uniform standard running across all operations. Each location is different; collecting and collating information in those locations is different; and where that is stored and who is reading it is different.
We aim to standardize that process across a global company so that there’s complete transparency and a uniform standard. With our data, operations managers can compare warehouses or locations across the world and assess what works best for their company.
Nuthi: What are the regulatory issues Dexory has faced and predicts to face as it continues to refine its technology and expand globally?
Danescu: We work in a new field, as autonomous robots have only been around for a decade or so, and the need for regulation is obvious. As such, new rules arrive in our sector constantly as regulators try to keep up with the rapid changes, and we do the same.
Robots weigh 100s of kilos, move autonomously, and operate alongside humans, so we’re extremely mindful of having the latest machine directives.
We also process information from different locations, so we ensure we’re transmitting that securely to customers and that different levels of users have different levels of access to company information.
We make sure we’re abreast of developments by being part of various working groups and constantly liaising with our customers and partners.
Nuthi: Dexory has previously praised the metaverse as a way to solidly explain the importance of data visualization and digital twin technology in the logistics industry. Could you explain why the metaverse will particularly benefit companies like Dexory?
Danescu: Creating digital twins has long been an aim for companies in industrial, primarily manufacturing environments, with digital modeling teams helping organizations map out their locations in more time-consuming, manual, and often less accurate forms. The metaverse has often seemed gimmicky, but in an industrial, logistical, or enterprise environment, it starts to make sense. With Dexory, robots continually scan locations, automating the previously cumbersome process. This opens up a wealth of options with the real-time information you can collect and store.
You can now know which pallet is in the wrong place in your warehouse immediately, what goods were damaged on delivery, or how to best maximize your space. On top of that, interesting case studies, more similar to the consumer metaverse companies like Meta are exploring, open up with training. You can show trainee staff your locations before arrival, train them on health and safety, and show them best practices, all inside their corporate digital twin. It’s an exciting one to watch as more and more opportunities open up.
