Driving efficiency in container logistics: "We want to become the superbrain of logistics"

Northbound, a startup initially backed and accelerated by DB Schenker and MVP Factory, secured €1.3 million in pre-seed funding. In this interview with the CEO of Northbound, we talk about how Northbound facilitates container logistics and optimizes the operational process flow for companies.

Northbound, an AI-driven logistics solution developed within MVP Factory's venture studio, is poised to transform the logistics sector. It aims to enhance efficiency, reduce costs, and optimize supply chain management through advanced AI technologies.

Marie-Christin Bergmann, Senior Communications Manager at MVPF, sat down with Andreas Canel, CEO at Northbound, to understand the journey of this innovative venture. In this interview, Andreas provides insights into the journey, the challenges faced, and the transformative potential of AI in logistics.

Key questions addressed include:

  • What inspired the creation of Northbound and what solutions does it offer to the logistics industry?
  • How were challenges overcome during the development of Northbound?
  • What impact will AI have on logistics, and how is Northbound leading this change?

Marie: Andreas, what problem are you solving with Northbound?

Andreas: Our main goal with Northbound is to reduce high demurrage and detention (D&D) costs for our customers, who are mainly international importers. These penalties occur when containers are left in one place for too long, whether inside or outside of ports. Many companies pay millions of dollars in penalties each year. Our SaaS solution helps them to minimize these costs by creating cost transparency and optimizing operational processes in response to accruing fees.

Marie: Why is this such a big challenge for many companies?

Andreas: The main problem is often a lack of data and visibility – with hundreds of containers arriving every week, it's easy to lose track of goods and their locations, leading to potential surcharges or missed delivery dates.

Today, teams are often still using Excel spreadsheets and manual effort to manage this specific part of the supply chain. One customer has described it as a “black hole” between their main systems and multiple actors, such as carriers, freight forwarders, warehouse staff, and planning teams. D&D rates are different with every carrier and in every port and teams struggle with keeping an overview of what's currently accruing. What's more, goods are sometimes sold while still on the ship. This means that one container can suddenly become much more important than another - priorities shift quickly.

With basic tools and no access to real-time milestone- and cost data, it’s hard to manage the varying levels of importance for individual containers, depending on what they're carrying and how costly they have become through collected D&D charges. Our tool helps coordinate and manage these container movements and optimizes the operational processes from arrival at the port via delivery to the warehouse until the empty container is returned.

Marie: What was your personal motivation for starting Northbound?

Andreas: My passion for process improvement started at Amazon, where I worked as a Senior Operations Manager in large fulfillment centers. It was always about working more efficiently and processing more volume while ensuring high quality and keeping delivery promises.

During my time there, I realized that having access to data in real-time was critical to making better operational decisions, and wanted to drive these innovations further - building a startup was the best way to achieve that. My ultimate goal is to make on-the-ground processes in logistics more efficient while acknowledging the deep level of real-world complexity which is too often disregarded. I also used to sail on commercial container ships with a captain’s license, so building Northbound is a return to my original industry that I value and know very well.

Marie: You are working with artificial intelligence, particularly in the area of invoice processing. How do you approach this and what is your vision for the future?

Andreas: We use AI to automate D&D invoice processing. While the deterministic part, such as counting the actual processing days of a container, is mathematically relatively straightforward, I believe that AI brings real benefits in more unstructured areas like invoice verification.

In application, this means that we process incoming invoices via image recognition and extract the relevant data - this involves understanding the invoice, checking the rates applied, and reconciling the milestones like container discharged and container returned to the terminal. Originally, these steps were carried out by humans, leading to high turnover time and error possibilities.

This is where our AI comes in: it reads the invoice, extracts the milestones, compares them with neutral sources, and checks the costs. This whole process, which would take at least 30 minutes manually, can be completed by our AI in just a few minutes. This not only improves the speed but also the quality and accuracy of the review.

Another benefit of AI is its flexibility. Traditional systems such as OCR rely on documents having a fixed format. However, our AI can dynamically respond to different invoice formats and read data more efficiently. This allows us to process a wide variety of invoices from different carriers, significantly increasing flexibility and customization. Another major advantage is that we are now able to actually understand the data within these documents, enabled by today’s Large Language Models (LLMs) which come with Natural Language Understanding (NLU). 

Marie: And what is your long-term vision for AI?

Andreas: Our long-term vision is to fully automate the decision-making process in container logistics using AI. We want AI to replace Excel-supported human decision-making and take over operational tasks by analyzing all available data and making optimal decisions. Imagine an AI that determines the best sequences and priorities for container movements in real-time, based on various criteria such as cost, delivery promises, and capacities.

Initially, it will be a human-machine combination, with AI making recommendations and humans checking and executing them. In the long term, however, AI could take on more and more tasks independently, similar to the algorithm at Uber that administers trips.

Marie: Very exciting! What are your next steps following the successful funding round?

Andreas: With the latest round of funding, we want to drive two areas in particular: Product development and market entry. 

First, we will hire more engineers to develop and improve our product. We are focusing on more granular data visibility and deeper feature design to meet the needs of our customers. Moreover, we have new pilots upcoming in the next months and will put our energy into generating maximum value for our customers. Direct contact with customers helps us to gather valuable feedback, which in turn flows back into product development.

At the same time, we want to expand our market presence. This means raising our profile and attracting more customers. We aim to keep the team nimble and focused to remain efficient and agile but make targeted investments where necessary.

Marie: What are your biggest challenges at the moment?

Andreas: Staying focused on the important issues and building the right team to push in the right direction - those are the main challenges. It's about finding the right people for the next crucial projects and making sure the team is optimally organized.

Marie: What milestones have you reached since the company was founded and what are you most proud of?

Andreas: A big milestone was getting our first paying customers. The transition from an MVP to a product that customers are willing to pay for was a big step. Our pilot project with a large German sporting goods manufacturer helped us tremendously, as it validated our concept and built trust. Another one was our successful pre-seed round. Despite a difficult funding environment, we managed to raise €1.3 million - this is an absolute validation of our business model and the market need for such a digital logistic solution. 

Marie: What have you learned from working with MVP Factory and DB Schenker?

Andreas: Working with the DB Schenker & MVP Factory Venture Studio provided us with exclusive access to the right knowledge and industry expertise. 

MVP Factory acted as a strong sparring partner from the beginning as we were surrounded by experienced professionals who had the knowledge of the ins and outs of business-building and deep ties into various start-up ecosystems. This is particularly helpful when you don't yet have your own large team to discuss strategies and next steps with. 

With DB Schenker, we got the opportunity to establish ourselves in the market and win strong new customers. Having direct access to industry experts from a major global logistics provider is invaluable for a supply chain startup. It has been extremely helpful to have these two strong partners on our side.

Marie: What advice would you give to other founders?

Andreas: Spend twice as much time ensuring that the problem you want to solve is relevant to your customers. It's not about finding a cool solution and then looking for a problem - the validation phase is critical. The closer you are to tangible money on the P&L, the easier it is to prove that the problem is important and support it with a solid business case.

Another important lesson is that everything takes longer and is harder than you initially think. Many tasks seem small but turn into substantial projects. Persistence and iteration are the keys to success. Stay resilient and steady - the greatest successes often come after a few setbacks and challenges.

Marie: Where do you see the journey going, Andreas?

Andreas: Our vision is to enable intelligent decision-making in operational logistics. We want to become the "superbrain" of logistics, seeing everything and orchestrating it optimally. We have deep operational expertise and we want to use it to unravel a significant change in the industry and solve relevant operational problems in logistics. 

Marie: Thanks for the interview, Andreas. It sounds like an exciting journey!

Andreas: Thank you, Marie. It was a pleasure!

Download "Translating product goals into business goals"

This was just a preview, you can unlock the whole content here. Enjoy!

Icon Form
Thank you for subscribing!
Check your email to confirm your subscription.
Oops! Something went wrong while submitting the form.