Arrive AI Inc.

Good morning, everyone, and thank you for joining us today. With me on the call are Dan O'Toole, Arrive AI's chairman, CEO, and founder, and Todd Pepmeyer, chief financial officer. The earnings press release issued this morning is available in the investor relations section of the company's website at arriveai.com. Before we begin, please note that today's remarks may include forward-looking statements regarding the future financial results, operations, and performance. These statements are not guarantees of future results and are subject to risk and uncertainties that could cause actual outcomes to differ materially. We encourage investors to review the risk factors detailed in ARRIVE-AI's SEC filings which are also available on the company's website. Now I'll turn the call over to Dan O'Toole.

Hey guys, Dan O'Toole, CEO of Arrive AI here. I want to thank you so much for joining our earnings call today. I'm really excited about where we are and the trajectory that this company is under. So I couldn't be more excited. I wanted to start out by saying that running Arrive AI has been the journey of a lifetime for me. and I would not trade one moment of it. And what I mean by that, true integrity dictates that acknowledging the challenges and the successes equally is what it's all about. Is anything ever straight up and perfect? Of course not. But you know what? That creates opportunities, and that's what this company is all about. I want you to know that I continue to be hyper-confident about where we are heading, how we're getting there. And I know that in the very near future, there's going to be a moment when a switch flips and things happen in a hyperscale way. But right now, we are super focused on prudently executing on our roadmap. As part of that roadmap, it's crucial to have the right people guiding your business. Our board of directors plays a key role every single day with their decades of experience and leadership across logistics, healthcare, finance, and now cellular networks. I'm really happy right now to announce Mike Fitz has just joined our board. Mike is the Vice President of Indirect Channels and Solutions Sales at T-Mobile for Business. He brings over three decades of experience in telecommunications, enterprise technology, and global network solutions. His insight into 5G, IoT, and partner ecosystems will be invaluable in accelerating our growth, and these are all areas that we are very focused on right now. It's a very timely acquisition to get Mike on our board, and I'm looking for some big things. I'm going to let CFO Todd Pettmire provide details on our financial results in a moment. But before that, I do want to stress that we are in a moment where new partnerships, deployments, and innovations have significant potential to drive material growth and revenue. And we have put together a dynamic sales team to execute on that every single day. Now, speaking of innovation, one of the areas we particularly are excited about is artificial intelligence. We believe AI will play a critical role in how packages move, how delivery networks operate, and how systems coordinate with one another in the future. So in the spirit of that, we decided to do something kind of novel today. I'm not sure that it's been done before, but we are going to have today's entire earnings call given to you in AI voices of the team that's reporting. We wanted to showcase in a small way how AI can be used as a practical tool to help communicate and operate more efficiently. Our leadership team will join the call shortly after, and we will all be live to answer your questions. But for now, let's begin with our prepared remarks voiced with AI. Kylie, why don't you go ahead and hit the play button and let's see what happens. When we founded Arrive AI and set out to change last mile logistics forever, it was a bold move. We started by shaping and building a market before it even existed, including... by securing patents that we believe provide a significant competitive advantage for the company. The logistics industry has spent billions of dollars trying to automate how packages move between trucks, drones, robots, couriers, but we are the first company to strictly focus on how and where these packages successfully and securely arrive. They need a home, and for that to happen, there has to be an infrastructure, that final exchange point, The secure handoff between sender, courier, and recipient is what we call the last inch of the last mile. That's the problem Arrive AI was created to solve. We are building the infrastructure layer for autonomous logistics. a network of intelligent delivery endpoints that allow people, robots, drones, and logistics providers to exchange goods securely. You can think of it as the shipping store at your door. Or said another way, if cell towers created the network for mobile phones, then Arrive AI is building the network for autonomous delivery. Next company progress. We kicked things off in 2020, and since then we have Raised capital through three successful crowdfunding campaigns. Completed our direct public offering in May. 2025, built a team of nearly 50 full-time employees. Began real-world deployments of our technology. Today, Arrive AI trades on NASDAQ under the symbol ARAI with approximately 47 million shares outstanding and roughly 52% insider ownership. That level of insider ownership reflects our belief in the long-term value we're building and closely aligns our leadership team with shareholders. Part of that long-term value comes from our robust portfolio of US and international patents, which is one of the most important assets we possess. Our patents protect the digital architecture around secure delivery endpoints, autonomous handoff between humans and machines, climate-assisted storage, chain of custody verification, and interoperability across multiple delivery methods. We recently secured our 10th patent, which allows multiple people to use the same secure arrive point. The patent was issued on March 31st, 2026 and protects the IP that enables our units to handle packages for many different users with built-in storage and sorting to manage deliveries and pickups efficiently. These units offer the same security chain of custody and communication features as a single arrive point, but are designed for shared use across multiple homes or businesses. Additionally, the patent advances the intelligence and coordination capabilities of our logistics platform. enhancing how secure delivery endpoints interact with drones, ground robotics, and human couriers. With these IP, protected capabilities, combined, the arrive point becomes the clear winner for an exchange point in the delivery ecosystem. And the more endpoints we have connected to that network, the more valuable the network becomes. That's the network effect. I saw a meme recently that drove this point home. You know what was better than the first telephone? The second telephone. The scale of our opportunity is enormous. In the United States alone, there are approximately 170 million delivery addresses, and this number increases by 4,000 addresses every day. Each of those locations receives packages, increasingly including items that require secure or time-sensitive delivery. like pharmaceuticals, medical supplies, groceries, lab samples, and high-value retail goods. An arrive point allows for unattended asynchronous delivery and pickup across these addresses, meaning each mode of delivery can come and go at its own cadence without waiting on a human or any other party to arrive. This prevents wasted time and increases efficiency and opportunity. Think of it this way. Right now, a ground robot can bring a delivery to you, but you have to be there to accept that delivery before it can move to the next. Or a drone might drop its package in a puddle-filled yard. Arrive AI solves these and many similar issues. With our solution, a robot can drop its package into our arrive point and immediately continue on its route. For drones, our network enables secure weatherproof delivery while optimizing routing so drones carry payloads on more flights, significantly reducing empty return trips. It can deliver your hamburger and at the same time pick up the shirt you need to return. One of the most important proof points of our progress is our live deployment with Hancock Health in Indiana. In that deployment, arrived points were installed between the Sue Ann Wartman Cancer Center and the hospital laboratory to support biospecimen transport using an autonomous robot. The route covers roughly a quarter mile round trip and supports multiple deliveries throughout the day. We recently released an in-depth white paper to explain our findings in detail. During this live deployment at Hancock Health, we demonstrated that our platform can seamlessly integrate into real-world hospital workflows while delivering measurable efficiency gains. We reduced staff walking time without adding steps and effectively extended staff capacity in a resource-constrained environment, freeing up their time for higher-value, patient-facing care. The system operated reliably within active care conditions reinforcing trust through consistent performance, and clear handoff signals. These results validate our ability to drive durable operational improvements in complex healthcare environments. You can find the white paper on our website for more details. Now, I'd like to speak briefly about our partnerships. Autonomous delivery is not a single technology. It involves robotics, drones, logistics platforms, and AI coordination systems. Rather than trying to build every one of those components ourselves, Arrive AI focuses on the network layer. We provide the secure endpoint infrastructure and orchestration platform, while partners provide delivery systems. For example, our partnership with Autonomy, a like-minded early-stage company that develops autonomous delivery robots, allows robots to integrate directly into arrive point deployments. This allows us to quickly evolve and refine how our network aligns with their hardware, iterating and adapting in real time for better efficiencies and processes from software to hardware. This ecosystem approach allows us to support multiple delivery technologies while we stay focused on building the network itself. We are also taking advantage of being a member in the NVIDIA Connect program. NVIDIA is proving to be an invaluable asset for our development by exponentially increasing our speed to deployment. Our engineers are using NVIDIA Blackwell workstations, allowing them to create models that are taking them hours instead of days, which has materially accelerated our development. I also want to provide some context on how our product development has evolved over the past year. Before we became a public company, Arrive AI had a relatively small engineering team working on what was essentially the third generation of our ArrivePoint platform, the AP3. When we went public, gaining access to capital allowed us to significantly expand our workforce. In fact, we were able to grow our team tenfold. Those additional engineers immediately began advancing the next generation of ArrivePoint technology, creating the AP5 platform. Today, we've brought all of those engineering teams together around a single objective, accelerating product development and refining the ArrivePoint platform as quickly and cohesively as possible. Instead of separate development tracks, we now have the full strength of our engineering organization focused on building, improving, and advancing the ArrivePoint platform together. Our development can now happen internally, leveraging the expertise of the team we've built while materially reducing our dependence on external resources. This has also allowed us to move faster, remove redundancies, reduce third-party R&D costs, and have more real-time quality control. For example, we've implemented AI simulations to support the growing ARRIVE network for the next generation AP5 platform while remaining backwards compatible with our AP3 platform, ensuring that both systems can work seamlessly together. Now, our goal is to convert these innovations into sales in the near future. We are advancing our conversations with organizations in the healthcare and manufacturing sectors with a goal of securing early stage deployment arrangements for both our AP3 and AP5 systems. With that, I'd now like to turn the call over to Arrive AI's Chief Financial Officer, Todd Pepmeyer, to talk through the financials and provide more background on our revenue model.

Thank you, Dan. When Arrive AI became a public company, we were clear that the early years would be about building the right infrastructure rather than maximizing short-term revenue. After all, infrastructure businesses require upfront investment. You build the network first, and revenue grows as that network expands. For the fourth quarter, our total revenue was $15,000, all of which was recurring subscription revenue. For the full year, revenue was just over $113,000. Our net loss for the fourth quarter was $2.7 million, compared to a loss of about $1.3 million in the same quarter of 2024. The increase was primarily due to higher operating expenses. For the full year, net loss was $12.8 million versus $4.5 million in the prior year. We ended the year with $2.1 million in cash on the balance sheet, and in January 2026, we executed a $10 million draw from our existing credit facility on favorable terms. This significantly strengthens our balance sheet and provides a meaningful runway to continue executing our business plan and funding our growth initiatives. Our quarterly cash burn rate of approximately $3 million has been mostly driven by increased hiring as we built out the team to support growth, and we expect that level of investment to moderate over time as revenue scales. These 2025 results are being filed within the 15-day extension we requested on March 31st, 2026. During our preparation of these financial statements, we discovered an error with the previous accounting treatment related to our convertible note payable financing. In short, the structure of the agreement creates a derivative instrument according to US accounting standards. This complexity required us to engage an independent expert to perform the complex modeling required to accurately fair value both the convertible notes and attached derivative instruments. As a result, we have subsequently applied the new method to our previously reported quarterly results. We expect to file amended reports for both the June 30th quarter and the September 30th quarter alongside the full year results. The net result of this change will be higher reported net income in the June 30th period and lower net income in the September 30th period. This change affects net income and the presentation of assets, liabilities, and stockholders' equity on the balance sheet. There is no cash impact. Revenue model. As we look ahead, our long-term revenue model has three primary components. The first is arrive point subscriptions where organizations like hospitals, laboratories, manufacturers, and enterprise campuses deploy arrive points as part of their logistics infrastructure. The second is network as a service revenue. As more endpoints are deployed, they connect into the Arrive AI network, enabling logistics providers to route deliveries between locations. The third and final revenue component is from data and AI insights. Autonomous logistics generates valuable operational data that can be used to optimize delivery networks. Over time, we expect our revenue mix to evolve toward approximately 50% network infrastructure revenue and 50% transactional and data-driven services.