Complete visibility is the key ingredient to success in today’s supply chain.
It is the reason why autonomous drones are becoming increasingly popular in warehouses. Drones allow warehouses to automate inventory counting seven to 10 times or even faster with higher accuracy and increased efficiency than manual counting.
Sientis links computer vision-based localisation, barcode scanning, full autonomy and multi-drone orchestration technology in one seamless warehouse management service. The company’s customers can benefit from detailed, up-to-date inventory analytics that reduces low-value manual labour and transforms productivity and efficiency. Overall, Sientis helps its customers improve overall efficiency with a minimum 40% return on investment over a three-year period.
Inside Sientis
Having originally been part of Nokia Bell Labs and also formerly named Nokia AIMS, the founding of Sientis began by looking at vertical farming and how to automate the analytics of plant health. This work then expanded into the warehouse space and eventually saw Sientis transition into its own autonomous business group.
“We are an internal startup that is being incubated by Nokia,” Paul Heitlinger, Venture General Manager, tells us. “Now, we are focused on providing the best possible solution for the warehouse industry for cycle counting by using our in-house developed autonomy stack for the drone. We do our own analytics and interpret the data. We are essentially a full-stack organisation from the image capture, the drone autonomy, the analytics and the UI – we do it ourselves with a really small team that is both very agile and smart, so we are able to develop these solutions quickly and efficiently.”
Heiltinger adds that his company builds its own products to best meet customer needs. “We’re always advancing, researching and moving the product forward and building the best possible solution for cycle counting,” he adds. “We are part of Nokia, so they are invested in this business. They believe that this is a growth business for the company.”
Lisa Mulholland was recently appointed Vice President of Sales at Sientis. She explains the company’s past few years have been filled with rapid growth and transformation fuelled by advanced technology. “With the tools that have been provided, the technologies have significantly improved analytics, automation, decision-making and are enabling businesses to optimise operations,” she reveals. “With these improvements, our Autonomous Inventory Monitoring Service (AIMS) division is transforming the space.”
Power of data
Data is a big piece of the puzzle for Sientis and its people. According to Heitlinger, one of the biggest advantages of leveraging new, advanced digital tools is the visibility over what customers want to see and what they actually need. “I think one of the powerful things about natural language is that we don’t have to predict what customers want to see,” he explains. “We will have models that are trained on specific kinds of data and they can use natural language queries to find the data they are looking for. It will really open up the reporting to what a customer wants to see.”
As a result, customers will have access to a powerful tool that can mean unprecedented access to Sientis’ data. Heitlinger explains that as long as the information his organisation provides is useful and can be interpreted from LLMs then it doesn’t matter how customers utilise the data.
“The other part is that we want to ensure that customers can access their data quickly too,” he adds. “One of the things that we are working on is digital twins, and we are doing this in conjunction with Bell Labs as well. How do we get customers an overview of their warehouse, where at a glance they can see all the missing inventory? How do we ensure that inventory analysis is provided as quickly as possible to customers so they can come in and find that missing inventory quickly? We are implementing digital twin solutions and natural language queries to ensure that customers get access to the data and how they want it in a really quick and efficient way. It’s not just a simple solution, it becomes a much more powerful solution because the customer decides how they want to see their data.”
Navigating disruptions
Given the nature of the complex world the supply chain faces today, things don’t always go to plan. Over the past half-decade or so, the world has encountered a series of ‘black swan’ events that have caused significant problems to companies and their supply chains. Geopolitical issues such as COVID-19, elections, wars, inflation and more have all had their own effect on global supply chains in one way or another and those that have overcome such challenges have done so by being agile, flexible and ready to respond quickly. Helping Sientis to do that has been through leveraging data analytics.
“The best warehouse operators are the ones that are going to manage their accuracy, their customer service, being able to ship on time and not lose inventory,” explains Heitlinger. “It’s important to let workers, who are a scarce commodity, do the higher value things like picking, shipping and packing, while letting Sientis do the work that no one else wants to do that is only done because of inaccuracies that humans cause. We’ll do it much more accurately, much faster and allow our customers to become the best warehouse operators amongst their peers.”
Mulholland adds that the importance of transitioning from a reactive to a proactive approach cannot be understated and she is already witnessing the seismic shift underway within the industry and beyond. “We’re starting to see the signs of the true value that these technologies hold and the full potential is still unfolding,” she tells us. “Many organisations are in the process of integrating these AI-powered solutions. Like Paul said, it reduces human error, cuts costs and enables data-driven decisions. As adoption increases, we’ll continue to see greater efficiencies, lower operational costs and enhanced supply chain resiliency powered by this technology.”
Setting boundaries
Over the past few years, GenAI and the potential it brings has become the name on most supply chain executives’ lips. This is partly a result of the rise of OpenAI’s ChatGPT model which has accelerated the topic of large language models and brought it to the forefront of conversations. However, one of the biggest concerns with chatbots is the possibility of hallucinations and how answers that aren’t true could be presented as fact. Fortunately, Sientis hopes to one day have an answer for that. The organisation is training its model on customer data and its technology is learning structured data.
“It’s not something that lends itself to hallucination,” says Heitlinger. “By the time we release it into production, it’s been thoroughly tested and trained. We beta-tested with customers first so nothing’s going out to production that we’re not completely happy with. It would be really bad if we released it and a customer said, ‘Tell me what my most lost product is’ and it was totally wrong. But it’s not dealing with complicated data either so there’s not loads of opportunities for these models to go wrong from my perspective.”
For Mulholland, one of the biggest considerations when introducing new ways of operating is determining what the practical value is. “It is important to have clear business objectives and align them with specific goals like cost reduction, efficiency, real-time visibility,” she explains. “One of the things that myself and my team pride ourselves on is getting to know our customers, the ins and outs of their business, and how our solution is tailored to their direct needs.”
The future
Looking ahead, Heitlinger believes the future of Sientis could go in several different directions. “We have drone autonomy, so there are always new opportunities that we can use our platform for,” he tells us. “The drone ultimately captures the data on the shelf at a customer site and the other half of this is around how we interpret that data and how we present it to the customer. There’s a lot of opportunity in the future.
“For our immediate future, we are going to continue to enhance the service. We really want to make the data as useful as possible for our customers. We are very agile, so we’re always built to what our customers want. One of the things that also differentiates us is that we look at all our customers as a partnership. We’re always trying to learn from our customers and trying to make our product better to help our customers operate their businesses better. We’re only successful if our customers are successful. It’s in our interest to listen to our customers and work with them on making our service to what they want and how they want to use it. The future is bright.”
Find out more about Sientis here.
- AI in Supply Chain
- Digital Supply Chain
