Edward Ryan
Analyst · William Blair
Thanks, Scott, and welcome, everyone, to the call. Today, we're reporting quarter -- record quarterly and annual financial results across the board. We're ahead of our annual plans and finished the year extremely strong. These are great results that I'm looking forward to walking through in more detail. However, first, let me give you a road map for this call. First, I'll start by hitting some highlights of last quarter, provide some comments on how artificial intelligence impacts our sector and business. I'll then hand it over to Allan and Ed Gardner, who will go over the Q4 annual financial results in more detail. After that, I'll come back and provide an update on how we see the current business environment and how our business was calibrated for Q1, and then we'll open it up to the operator to coordinate the Q&A portion of the call. So let's start with the fourth quarter and year that ended January 31. Key metrics we monitor include revenues, profits, cash flow from operations, operating margins and returns on our investment. For this past quarter, we again had record performance in each of those areas. Total revenues were at a record high of $192.8 million, up 15% from a year ago. Record high services revenues were also up 15% from a year ago, with our continued focus on generating recurring revenues. Record net income was up 22% from a year ago. Record income from operations was up 25% from a year ago. Record adjusted EBITDA was up 18% from a year ago. Our adjusted EBITDA margin is at a record high level of 46%. We generated a record high of $76 million in cash from our operations, up 25% from a year ago. So strong record results across all these key metrics. For the year, the results are equally impressive. Record revenues up 12% with service revenues up 15%. Record net income up 14%, record income from operations up 16%, record adjusted EBITDA up 16%, record cash from operations up 21%. As I said, all results for the year were ahead of our plans. At the end of the year, we had $356 million in cash, and we were debt-free with an undrawn $350 million line of credit. We remain well capitalized, cash generating, growing and ready to continue to invest in our business. We also have a normal course issuer bid that allows us to purchase up to 8.6 million shares before December of 2026. We made some small initial purchases before we went into a trading blackout in January. So a tool that we have that we've already used and that may be used again as we monitor rather volatile recent market conditions. I'm not going to spend much time talking about the operating results for the quarter or year. As I said, they were very strong. The reasons why are similar to what we've done in the past in the previous 2 quarters, first, we saw strength in the global trade data and intelligence from a chaotic tariff and sanctions environment. Second, we saw strength in real-time visibility and shipment tracking as we continue to leverage AI tools and agents to have the industry's leading shipment tracking rates. And third, we saw strong e-commerce imports in the United States, which was good for us as we have the market's leading solutions for helping with high-volume rapid customer clearances. We also completed a tuck-in acquisition in our e-commerce pillar earlier today. U.K.-based OrderMine is a current partner of Descartes with its solutions already working alongside our Peoplevox e-commerce, WMS for U.K. customers. We're particularly excited to introduce OrderMine's core product ForecastMine to our e-commerce customers around the world. ForecastMine is a strategic step forward in our e-commerce AI investments, accelerating our AI-powered forecast and demand planning, particularly for e-commerce sellers using Shopify. E-commerce sellers are focused on freeing up cash, protecting margin and scaling without operational drag. We've got a huge pool of rich inventory, order, supplier, fulfillment and returns data that ForecastMine can train on to help sellers do this. Specifically, it helps convert e-commerce signals into clear, actionable insights that reduce excess inventory, prevent stockouts, improve forecast accuracy across channels and seasonality, automate purchasing and shortened planning cycles from days to minutes. I'd like to welcome the OrderMine team to Descartes. I'm happy to answer questions on any aspect of our operations or the acquisition later in the call or afterwards. However, I wanted to spend some time today with some comments about what I'm getting asked the most questions about the impact of artificial intelligence on our industry and on our business. I've heard market commentators raise concerns about the impact of artificial intelligence technologies on the long-term prospects and terminal values of technology businesses. Specifically that if AI can generate software code, then coding becomes commoditized and established technology companies are vulnerable to new entrant competitors or companies taking software coding in-house. In short, the headlines are AI could kill existing technology companies. I don't buy any of that. Those commentators are fundamentally misunderstanding the value technology companies bring to customers. I believe AI technologies will make businesses like Descartes even more valuable to customers. At the heart, technology businesses do not exist to just make software code. This is not the value they deliver to customers. Instead, they deliver a comprehensive service to customers, a service that includes security, trust, stability, compliance, infrastructure, operational and customer support, workflow and domain expertise, proprietary data, connections, scale, innovation, cross-pollination of valuable ideas and yes, technology functionality that is powered by software. Generative AI doesn't replace all those things. Generative AI is a tool that allows tech companies to make many of those things better and deliver them faster. Tech companies will leverage AI to make their businesses more secure with AI tools that help identify, diagnose and prevent attacks, they'll make their service availability more reliable with AI tools across their infrastructure, and they'll enhance operational support for customers with AI-powered agents to address routine increase. Generative AI companies know the market is making a mistake by questioning the long-term prospects of technology companies. They're admitting that publicly, and they're running their own businesses by relying on specialist technology businesses rather than using their own AI tools to build an inferior quality enterprise system. The market peers don't match reality. I've also seen market commentators paint many technology businesses with the same brush that the impact of AI will be the same for everyone. That's also not true. The impact of AI will vary significantly by industry, business model, scale, pricing model and investment commitment. So let me talk to Descartes specifically. What we are, what protects us, the moat around our business, and the opportunities that AI brings to our business. First, what we are? Descartes is a network services business. We run the global logistics network. It's the world's largest connected community of supply chain and logistics participants, formed over more than 30 years. It's relied on by the community every day to process billions of transactions per year. We use technology to help our customers solve complicated inter-enterprise supply chain and logistics problems on the GLN that require the cooperation of multiple parties and communities on the network. We're not an enterprise software company. Now let me describe the huge moat we have protecting our business. I'm going to try and help you wrap your arms around how broad it is by putting into some key categories. First, we're a critical network relying on by the world. As I said, the Global Logistics Network is relied on by the community every day to process billions of transactions per year. It's unparalleled uptime breadth, speed and specialization make it critical to the operations of our more than 30,000 customers. It's difficult and time consuming for another company to replicate that. It's challenging for our customers to find something as reliable, relevant and comprehensive to switch to. It's the major moat for our business. Two, we help solve complicated inter-enterprise challenges. Supply chain and logistics challenges are not enterprise issues that can't be solved with just a customer's internal people and data. Supply chain and logistics challenges require interaction with external parties beyond the enterprise whether they be drivers, warehouses, customs authorities, governments, shippers, carriers, logistics intermediaries or banks. If you use AI to create tools or applications to help you, you still need to connect to the supply chain and the logistics world. That means you either connect once to the GLN or you connect and maintain hundreds or thousands of connections to external parties by yourself. The enterprise nature of our business keeps us relevant and makes us a better choice for our customers than trying to do it themselves. Third, we process transactions. Descartes is primarily a transaction processor as things are processed by the GLN, such as tenders, bookings, loads, invoices, bills of lading, customs filings, security filings, et cetera, we charge for our services. Our value is generally tied to the service we provide rather than the number of employees our customers may have now or in the future. Our model is not reliant on seat-based or user licenses. Four, we help with compliance. Many of our customers use our GLN to help them comply with various laws and regulations. This could include customs filings, security filings, tariff classification, foreign trade zone, warehouse operation, sanction party screening or public freight rate management. Customers are often wary of taking compliance burdens on solely themselves, especially given the pace of change of regulations and the financial and other consequences of getting it wrong. If we earn our customers' trust to reliably help them comply, then there's not much financial or other benefits to them changing something that's already secure, timely and accurate. This helps protect our business from new entrants and customers considering taking on compliance burden themselves. It also helps us grow because when we're a trusted and reliable partner for one compliance initiative, our customers are much more likely to trust us with other initiatives in the future. Five, we were a system of record. For many of our customers, our systems are the official trusted source of truth for their critical supply chain and logistics data. Using the Global Logistics Network, we help them ensure data integrity, accuracy and security of key supply chain and logistics information that they rely on for daily operations. This makes these customers very reluctant to switch to another provider or to do it themselves. Six, we are supply chain and logistics experts. We're in a very specific market. Our team lives, eat and breathe supply chain and logistics every day. When changes happen, and they happen quite often these days, you want to know that you're doing business with an expert that's on top of things. Our customers consider this expertise a part of our service offering, and it makes them dedicated Descartes customers. And finally, we're trusted, financially stable and transparent. We have a very good reputation. We've worked for many years to cultivate trust with our customers through reliable service, fair pricing, secure operations and continued expansion and innovation. We've built a financially stable business that our customers can be confident will be here for the long term. They have access to our public quarterly financial reports to monitor the strength of the business. All these things protect us from customers considering switching to companies with less operational history, reliability or financial stability. Our customers value our success. Now to the huge opportunities for Descartes with AI. We're actively investing and delivering results to our customers. Let me hit the 3 biggest areas of opportunity for Descartes. Our biggest opportunity with AI comes from the data on the Global Logistics Network. Descartes has the largest trove of real-time supply chain and logistics data in the world. We process billions of transactions a year. We have massive amounts of clean historical and real-time information on the sourcing, storage, classification, transportation, tracking, pricing, service history and financial settlement of most transactions in the global logistics and supply chain markets. AI technologies need data to function. AI technologies are trained and learned from consuming massive amounts of data. AI technologies are only as effective as the data they consume and only as relevant as the time lines -- of the timeliness of the data they get. Most AI technologies are all trained on the same publicly available information on the Internet. The real value is being able to train AI technologies using nonpublic information, which is exactly what information we have on our Global Logistics Network. Our Global Logistics Network data is rocket fuel for AI. We'll continue to grow and cultivate data on our GLN in a responsible way that allows our customers to benefit from the collective intelligence of the network. For us, our key focus going forward is respecting, anonymizing and protecting the data we have while preparing for how our customers may want to use it with newer AI technologies. Second area is that we believe AI agents will change the future of who uses our technology. We think it will change both what we sell to some customers and how we support them. We think an AI agent -- think of an AI agent as a digital coworker trained to do a specific task. AI agents are excellent for reducing human workload by automating repetitive tasks. They are also helpful to handle matters that aren't affordable to have humans do. Historically, our services have been designed to only be used by human workers often clicking on icons and entering data. However, that isn't the future. We're preparing our services to be used by either human or digital workers. Our customers expect value from digital workers. They don't want inefficiencies in their business from humans doing low value or repetitive tasks that could otherwise be automated. Rather, they want AI agents performing tasks and supporting humans who are making decisions. We believe this is real and current customer demand for us to meet. I believe our business will shift in 3 ways. We'll provide customers the ability to get AI agents and digital workers through Descartes. We're already doing this in areas of our business like MacroPoint. In MacroPoint, you can hire a digital worker to call drivers and get a location check on where the shipment is, another digital worker to gather missing shipment documents for you, and yet another worker to address data integrity issues. Each of these AI agents grow our network, improve the quality of the data the GLN has, and reduce costs for our customers. We'll arm human workers with the information they need to make decisions rather than to perform tasks. User interfaces are going to change, screens with complicated series of clicks and reports will change to specific information needed by human eyes to help make a decision. Finally, services will be designed to be consumable by AI agents, whether they are Descartes agents for our customers' own AI agents, our services need to be consumable in a machine-to-machine format. This may include providing AI agents access to different types of data in novel ways or enabling AI agents to interact with our own digital workers or technology. We believe AI agents will be part of the future for Descartes and our customers. We're already delivering value to our customers with AI agents and investing in delivering suites of digital workers that can help our customers. In addition to the AI agents I described with MacroPoint, these include: natural language searches and AI agents for Descartes GLN data mine U.S. import business; AI agents to help deal with challenging match scenarios for denied party screening on parties with ambiguous names and addresses; AI agents helping determine free trade eligibility based on past practices, helping our customers reduce their tariff bill; AI agents making automated tariff classification suggestions for goods; and using AI agents to interpret lengthy carrier rate agreements and present optimal selection recommendations, and there's many more. And finally, the third opportunity for Descartes is to make our business more efficient. We run a multinational, multicurrency, multi-pillar business. We operate an enormous distributed technology infrastructure that can be a target for attack from bad actors. We operate and monitor hundreds of products and services at elite availability levels. We provide support to and build more than 30,000 customers. We grow our business 10% to 15% a year, and have historically added 3 to 4 new businesses to the Global Logistics Network by acquisition every year. With that footprint, there are opportunities to improve our business with automation. We've invested into AI technologies to do this. Key examples are AI tools helping our software engineers with initial coding, customer support automation to enable customer self-help for routine inquiries, advanced AI technologies to harden our network security posture and new tools to monitor network performance. We're investing in AI technologies to help our team. We will get more efficient. However, our customers expect that we can reinvest savings generated by AI technologies into further improving the GLN and/or reducing our need to hire at the levels we have historically. That seems like a sound approach to me. Overall, AI is a tremendous opportunity for us. We believe it will spur further demand for our trusted real-time clean formatted GLN data and the collective intelligence of the network. It's already allowing us to deliver additional value to our customers with AI agents, and it's helping make our business more efficient. We believe that the interenterprise scale network infrastructure of our business puts us in a much better position to benefit from AI than legacy or emerging point or enterprise technology solutions. And finally, to wrap up, Q4 and FY '26 were very strong financial results for us. I'm excited about how the business is performing and the opportunity we have in front of us. I'm now going to hand the call over to Allan in the CFO role for the last time on one of these calls as we conclude the year. The good news is that Allan is going to remain a part of our business, and it's a privilege to be able to keep working with him. Ed Gardner will be the new CFO following this call, and he also gets the benefit of Allan's experience and wisdom as we make this transition. Ed Gardner is also on this call and available for investor and analyst questions afterwards along with both Allan and me. So with that, I'll turn the call over to Allan to go through the financial results in more detail. Allan?