Kodiak AI (KDK) Q1 2026 Earnings Transcript

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Date

Thursday, May 7, 2026 at 5 p.m. ET

Call participants

• Founder and Chief Executive Officer — Don Burnette
• Chief Financial Officer — Surajit Datta

Takeaways

• Capital raise -- Announced $100 million equity financing via PIPE with warrants priced at $6.00, providing net proceeds of approximately $95 million and extending liquidity into 2027.
• Deployment expansion -- Deployed eight additional driverless trucks, reaching a fleet of 28 trucks, with plans to exit Q2 in the mid-thirties and full-year guidance unchanged.
• Operational scale -- Achieved over 23,500 paid driverless hours, a 120% increase from Q4, surpassing all driverless hours recorded in 2025 during Q1 alone.
• Freight delivery -- Delivered cumulatively more than 15,600 loads and over 200,000 tons of freight in Q1, representing approximately 24% growth in loads delivered.
• Revenue -- Reported $1.8 million in Q1 revenue, up 74% quarter over quarter, mainly driven by increased driver-as-a-service adoption.
• Operating loss -- GAAP operating loss was $37.9 million, with a non-GAAP operating loss of $31.8 million, primarily due to continuing investment in research and development.
• Free cash flow -- Q1 free cash flow was negative $35 million, outperforming internal expectations; 2026 full-year guidance improved to a range of negative $155 million to negative $165 million.
• Cash position -- Ended Q1 with $90 million in cash, cash equivalents, and marketable securities; pro forma cash after the capital raise is approximately $185 million.
• Major partnerships -- Entered a strategic partnership with General Dynamics Land Systems for military ground vehicles and expanded a collaboration with Bosch for scalable industrial deployment.
• Long-haul autonomy progress -- Long-haul autonomy readiness measure (ARM) increased to 86% as of April, with management expecting accelerated progress toward a 100% target.
• Commercial network milestone -- Surpassed 25,000 commercial miles, with a network now exceeding the Earth's circumference.
• Product development -- Launched Model Context Protocol (MCP) servers for company-wide AI tool adoption, enabling faster development and deployment of bespoke AI solutions.
• Sensor platform -- Announced adoption of the NVIDIA DRIVE Hyperion architecture and showcased new SensorPod hardware with Bosch at ACT Expo.
• Customer wins -- Secured new commercial freight lanes with Rail Transport and initiated a pilot with West Fraser for Canadian forestry applications—Kodiak AI's first international and flatbed trailer pilot.
• Atlas platform transition -- Atlas to migrate to a new OEM platform from Q3, shifting to more economical day cabs and maintaining a target to fulfill the initial 100-truck commitment by H1 2027.

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Risks

• Chief Financial Officer Surajit Datta said full-year 2026 free cash flow is expected to remain negative, within a guidance range of negative $155 million to negative $165 million.
• "As we said in the remarks, we expect the second half of 2026 to look very similar to the first half in terms of raw numbers. We do expect the ramp of the trucks to accelerate quarter over quarter through 2027," potentially indicating slower near-term scaling before an expected ramp in 2027.
• Delivery timing for the Atlas platform transition will remain "closely aligned with our customers' needs" and dependent on procurement, deployment schedules, and hardware supply. This may cause variability in deployment rates.

Summary

Kodiak AI (NASDAQ:KDK) secured $100 million in equity financing to reinforce its balance sheet and support ongoing scaling efforts as it expands its driverless deployments, partnerships, and global reach. Management highlighted a surge in operational activity, with paid driverless hours and freight loads sharply increasing, and noted progression toward full deployment readiness for long-haul autonomy. Product and engineering innovations included new AI-powered internal tools, adoption of NVIDIA's next-generation compute, and expanded collaborations with General Dynamics Land Systems and Bosch. Management articulated expectations for steady commercial growth, citing new pilot projects in Canada and evolving customer needs, but flagged transition periods and ongoing investment requirements that will continue to impact cash flow over the coming quarters.

• CEO Don Burnette said, "We plan on submitting our application for a California testing permit in the coming weeks," targeting regulatory clearance for coast-to-coast deployment.
• Chief Financial Officer Surajit Datta reported that the $100 million transaction "priced at a discount" to facilitate speed and certainty, with warrants issued at $6.00 and common shares at $6.50.
• Commercially, all current Rail Transport moves operate on Kodiak AI-owned trucks with an observer in the cab, not yet fully driverless in that application.
• Defense business pipeline may expand as the President's fiscal 2027 defense budget includes over $50 billion for autonomous warfare groups, a substantial increase from the $225 million allocated in 2026.
• The company's modular, platform-agnostic software stack remains central to deployment agility, accommodating shifting customer preferences and varied hardware platforms.

Industry glossary

• PIPE (Private Investment in Public Equity): Negotiated, direct capital raise where institutional investors purchase company stock, often at a discount, with or without attached warrants.
• Model Context Protocol (MCP): Kodiak AI's company-wide AI architecture enabling bespoke tool development using unified data access for custom AI agents.
• ARM (Autonomy Readiness Measure): Internal metric used by Kodiak AI to assess technical and operational preparedness for fully driverless long-haul commercial launch, targeted at 100% for deployment.
• SensorPod: Modular hardware assembly that integrates sensors (camera, radar, LiDAR) on Kodiak AI vehicles.
• Drive-as-a-Service: Business model where Kodiak AI provides autonomous driving capability to third-party trucking fleets, charging for usage rather than hardware sales alone.
• NRE (Non-Recurring Engineering): One-time R&D expenses related to product design changes, cited in reference to hardware unit cost improvements.

Full Conference Call Transcript

Daniel Goff: Thank you, and welcome to Kodiak AI, Inc. Common Stock's first quarter 2026 earnings call. On the call today are Don Burnette, Founder and Chief Executive Officer, and Surajit Datta, Chief Financial Officer. A press release and an earnings presentation were issued earlier today and are posted on the Investor Relations section of our website. This call is being broadcast live via a webcast and a replay will be available on our website after the call. Before we begin, I would like to remind you that during today's call, Kodiak AI, Inc.

Common Stock will be making forward-looking statements within the meaning of the federal securities laws about financial performance and future events, including our guidance for fiscal second quarter and full fiscal year 2026, as well as our long-term goals. Actual events or results could differ materially. Please refer to our SEC filings, including our most recent Form 10-K and the Form 8-K filed with today's press release, for important risks and other factors that may cause our actual results to differ from those in our forward-looking statements. Additional information will also be set forth in our quarterly report on Form 10-Q for the quarter ended 03/31/2026.

We disclaim any obligation, except as required by law, to update or revise any financial or operational guidance and long-term goals or our other forward-looking statements, whether because of new information, future events, or otherwise. Any forward-looking statements made on this call speak only as of the date of this call. Further, in addition to discussing results that are calculated in accordance with generally accepted accounting principles, we also refer to certain non-GAAP financial measures. For more detailed information on our non-GAAP financial disclosures, including reconciliations to the most comparable GAAP measures, please refer to our earnings release, which can be found on our Investor Relations website. I will now turn the call over to Don. Please go ahead.

Don Burnette: Good afternoon, and thank you for joining us. Before getting into our Q1 results, I am excited to highlight that today we announced a $100 million capital raise. With our strengthened balance sheet, we believe we have extended our liquidity into 2027, which will enable us to support the next phase of growth as we scale our driverless deployments. Now I would like to turn to our Q1 results. In the first quarter, we increased both the scale and productivity of our growing driverless deployment, expanded our partner ecosystem across the long-haul, industrial, and defense verticals, and made meaningful progress toward our driverless long-haul launch targeted for late 2026.

We also made significant progress maturing our physical AI-powered technology and product while maintaining financial discipline and capital efficiency. We deployed eight additional trucks in Q1, for a total of 28 driverless trucks, further expanding our industry-leading driverless truck deployment. As of quarter end, those trucks have driven more than 23,500 paid driverless hours, a 120% increase from the end of Q4 of last year. These hours are equivalent to over a decade of working as a truck driver. Further, the hours driven in Q1 exceeded all the driverless hours driven in 2025. Over the same period, cumulative loads delivered increased to more than 15,600, representing approximately 24% growth.

That includes more than 200,000 tons of freight—approximately the weight of the Sears Tower—delivered in Q1 alone. We believe these results demonstrate that we are successfully scaling our product and delivering increasing value to our customers. Because Kodiak AI, Inc. Common Stock's integrated platforms are powered by a single autonomous stack, the capabilities we develop, the miles driven, and the new customers and partners we work with create a compounding flywheel effect benefiting long-haul, industrial, and defense applications. In the first quarter, we made strong progress on strategic partnerships and customer engagements as industry leaders continue to choose the Kodiak AI, Inc. Common Stock driver to enable their autonomous future.

I would like to highlight one exciting announcement we made earlier today: a strategic partnership with General Dynamics Land Systems, or GDLS, to collaborate on autonomous military ground vehicles. GDLS, part of the Fortune 100 General Dynamics Group, manufactures critical platforms such as the M1A2 Abrams tank and the Stryker combat vehicle. Working with GDLS will allow us to extend our reach into the core of the defense ecosystem. It also demonstrates our flexible approach to defense engagements. We are working with industry leaders to support paths to production and revenue, while simultaneously contracting directly with the Pentagon, as we have done with the Marines' Rogue Fires program. Our work with General Dynamics Land Systems is already generating results.

In March, we unveiled the first vehicle we developed in collaboration with GDLS: the Leonidas autonomous ground vehicle. The Leonidas AGV combines a Kodiak AI, Inc. Common Stock driver with EVerest's cutting-edge high-power microwave system for counter-drone operations, supported by GDLS' system integration expertise. We continue to make significant progress on our core technologies. Driving this progress is our increasingly aggressive adoption of AI tools that are proving to be true force multipliers across our company. AV developers are only as good as the tools they use, and AI is enabling us to develop new, powerful tooling that is already transforming how we work.

In Q1, we launched company-wide Model Context Protocol, or MCP, servers that allow AgenTeq AI tools to connect to all of our company data sources, allowing the entire company, not just engineering, to develop new bespoke AI-powered tools tailored specifically to individual needs. In layman's terms, these MCP servers and related data pipelines empower our team to use plain English to build AI tools and proliferate AI agents that massively increase our productivity, efficiency, and problem-solving capabilities. This, in turn, is driving a transformation in how we run our business.

For example, we have used our MCP service to develop PRISM, a flexible new tool that allows anyone in the company to search across thousands of hours of unstructured driving data using only text prompts, surfacing patterns and root cause analysis that previously required dedicated engineering effort. PRISM can explain the Kodiak AI, Inc. Common Stock driver's behavior in intuitive ways to both technical and nontechnical teams using natural language. We have used this new capability to tune the Kodiak AI, Inc. Common Stock driver in ways that would not have been possible before. For example, we use PRISM to not only identify commonalities among challenging highway scenarios, but even identify potential improvements that we have since adopted.

But these tools are not only about software. They also help to drive improvements in hardware, manufacturing, and beyond. On the hardware side, we announced that Kodiak AI, Inc. Common Stock will use the NVIDIA DRIVE Hyperion architecture in the next generation of Kodiak AI, Inc. Common Stock driver-powered trucks. We believe this will increase our ability to deploy even more capable and efficient driverless trucks over time. Additionally, at CES in January, we laid out our vision for industrializing the Kodiak AI, Inc. Common Stock driver through our strategic collaboration with Bosch, one of the world's leading automotive suppliers. Through this collaboration, we will leverage Bosch's manufacturing expertise to deploy driverless vehicles at scale.

This week, at ACT Expo, we demonstrated the progress we have already made together, exhibiting an early Kodiak AI, Inc. Common Stock SensorPod outfitted with Bosch camera and radar sensors. Taken together, these partnerships enhance the ecosystem needed to efficiently scale simultaneously across all three verticals, from vehicle platforms to industrialized hardware to AI compute. With that, I would like to discuss our progress toward our targeted driverless long-haul launch in late 2026. As of April, our long-haul autonomy readiness measure increased to 86%, reflecting steady progress in launch readiness. As we leverage our increasing investments in our team and AI tooling, we believe that our ARM progress will accelerate in Q2 and beyond.

Over the course of the quarter, we completed numerous safety case claims, including claims covering our driverless long-haul sensor field-of-view requirements and our redundant braking subsystems. As a reminder, completing a safety case is about collecting sufficient evidence to demonstrate safety, and Kodiak AI, Inc. Common Stock is one of only a small handful of AV companies that have successfully built a safety case and launched driverless operations. We continue to hone our safety case structure as we refine our safety processes and implement our learnings from our long-haul, industrial, and defense operations. To reach an ARM of 100% and unlock long-haul driverless operations, we will continue to gather evidence to close our remaining claims.

That work leverages the safety methodology, testing, and documentation processes we established over our nearly 18 months of driverless operational experience in the Permian. In addition to our work on the safe launch of our long-haul driverless product, we continue to expand our long-haul commercial operations, delivering freight with leading shippers and carriers from our Dallas hub. This afternoon, we announced that we launched service with a new carrier, Rail Transport. Through our collaboration, we are hauling freight with Rail Transport between Dallas and Houston four times a week. Rail Transport is one of North America's safest trucking companies, as recognized by the American Trucking Associations, or ATA.

They are a recent recipient of the ATA's President's Award, the trucking industry's highest safety honor. They specifically chose Kodiak AI, Inc. Common Stock because of our shared commitment to safety. During Q1, we also began freight services between Dallas and El Paso in cooperation with one of our long-term customers. This freight lane is our second route beyond a single hours-of-service after Dallas to Atlanta. It is just the kind of long-haul lane where the Kodiak AI, Inc. Common Stock driver can offer the most value, given the challenges fleets face staffing these routes. These true long-haul freight operations are critical to helping us build a product that meets our customers' needs.

We are working closely with all of our long-haul customers to prepare them for driverless operations in the coming quarters. While preparing for long-haul driverless represents our core focus in 2026, our industrial business demonstrates how our driverless technology is continuing to deliver value to our customers and expanding to other geographies and use cases. Today, I am excited to announce our planned pilot operations with West Fraser, one of the world's largest wood products companies, to demonstrate the Kodiak AI, Inc. Common Stock driver in logging operations in Canada. This will mark our first pilot in the forestry industry, our first international expansion, and initial operations with flatbed trailers.

Logging routes, like oil and gas routes we see in the Permian, are among the most demanding environments in trucking. We believe this pilot will further demonstrate the versatility of our system across geographies and trailer types and expand the range of industrial use cases where the Kodiak AI, Inc. Common Stock driver can deliver value. In addition to our new pilot in Canada, we continue to make meaningful progress on our Atlas deployment. Since we are not reliant on HD maps, we can quickly add new routes to our operational design domain. To date, we have delivered on over 15 unique routes with Atlas, each with its own complexities.

We also expect to continue to execute against our initial 100-truck commitment with Atlas over the next several quarters and expect to exit Q2 with driverless trucks in the mid-thirties. Atlas is evaluating deploying the Kodiak AI, Inc. Common Stock driver on a new OEM for the remaining trucks. This transition, beginning in Q3, will include a shift to a more economical day cab from a sleeper berth, which we believe will be the predominant configuration for driverless operations across both industrial and long-haul. We believe our modular, platform-agnostic architecture positions us well to support this transition efficiently, and we are working closely with Atlas to meet their evolving fleet requirements.

We view this as an exciting opportunity to demonstrate the ease of integration of our technology on an additional truck platform. Delivery timing will remain closely aligned with our customers' needs and will depend on factors such as procurement of the new truck platform, fleet planning, deployment schedules, and critical hardware and truck availability and lead times. As a result of this platform transition and associated procurement timelines, we now expect to deliver a similar number of trucks in 2026 as we expect to deliver in the first half. As the new platform scales, we expect deployment to accelerate. We anticipate completing Atlas's initial 100-truck commitment in the first half of 2027. Now turning to defense.

With General Dynamics Land Systems and beyond, we continue to add wins in the defense vertical where reliability and performance in complex environments are mission-critical. At the broadest level, we are seeing the defense autonomy ecosystem evolve from experimentation to deployment, as ongoing geopolitical instability forces both the Pentagon and our allies to accelerate their timelines for frontier technologies like autonomy. Underlining this increased interest, the President's 2027 defense budget includes over $50 billion in funding across land, air, and sea for defense autonomous warfare groups, up from just $225 million in 2026. We therefore expect to see increased revenue-generating opportunities in 2027 and beyond.

Our recent successes in defense demonstrate the maturity and adaptability of our system in mission-critical environments, and we believe will position us well as the Pentagon increasingly turns to commercial partners to accelerate autonomous ground vehicle deployments. Moving on from defense, Q1 saw continued regulatory progress for the autonomous vehicle industry. We are encouraged by continued momentum toward a more consistent federal approach, which we believe will further support broader adoption over time. At the state level, California recently published final state regulations that will allow us to deploy the Kodiak AI, Inc. Common Stock driver in our home state, thereby enabling us to offer coast-to-coast driverless service. These regulations will provide us with additional regulatory certainty.

We plan on submitting our application for a California testing permit in the coming weeks. Similarly, Texas also launched its new AV permitting program. After submitting our first responder interaction plan to state officials, we received our Texas AV authorizations. We continue to engage with regulators at both the state and federal level. One engagement of note was our participation in a grant-funded public demonstration in cooperation with DriveOhio, the Ohio Department of Transportation's hub for smart mobility technology. Our work with DriveOhio represents Kodiak AI, Inc. Common Stock's first operational deployment outside of the Sunbelt and enabled us to demonstrate our long-haul autonomous solution to policymakers and industry leaders in Ohio and Indiana.

As we prepared for this engagement, we passed an exciting milestone: we added our 25,000th mile to our commercial network, which is more than the circumference of the Earth. The massive size of our network underlines the flexibility of our routing technology, which enables us to quickly add new routes across a range of geographies and deployment types. In closing, we believe our $100 million equity financing combined with our continued product maturation and driverless deployments positions us to scale driver-as-a-service across long-haul, industrial, and defense in a disciplined and capital-efficient way. We are well on our way to scaling Kodiak AI, Inc.

Common Stock into a sustainable business that provides real value to customers, and I am excited by the opportunity ahead. I would like to take a moment to thank all of the Kodiak AI, Inc. Common Stock team members who worked so hard in the first quarter to drive us forward. Autonomous driving is the first wide-reaching application of physical AI. This is just the beginning. Now over to Surajit.

Surajit Datta: Thank you, Don, and good afternoon, everyone. I am pleased to share Kodiak AI, Inc. Common Stock's financial results for 2026. We delivered a strong first quarter across both operational and financial metrics, successfully executing against our strategic priorities: scaling driverless deployments, growing recurring revenue, and maintaining disciplined spending. We ended Q1 FY2026 with 28 driverless trucks, in line with our expectations, as we continue to broaden our deployment with our existing industrial customer. Q1 revenue was $1.8 million, representing 74% growth quarter over quarter. This performance was primarily driven by continued expansion in driver-as-a-service revenue enabled by growth in customer-owned driverless trucks. GAAP operating loss for the first quarter was $37.9 million.

Non-GAAP operating loss, which excludes stock-based compensation, was $31.8 million, primarily reflecting continued investment in R&D and operational support as we scale our deployments. We incurred capital expenditures of approximately $5.5 million, primarily related to AV hardware that we deploy on our customers' trucks. Turning to cash flow, Q1 free cash flow was negative $35 million, outperforming our expectations. This reflects continued investment in R&D, operational scaling, and AV hardware deployment, partially offset by improving operating leverage. For 2026, we expect driverless trucks to increase to the mid-thirties.

We expect free cash flow of negative $39 million to negative $41 million, with the increase primarily driven by non-recurring spend for hardware unit cost improvements and incremental CapEx to support driverless long-haul testing and development. For the full fiscal year 2026, we are improving our free cash flow guidance and now expect free cash flow to be in the range of negative $155 million to negative $165 million. This improved outlook reflects continued growth in revenue, expected lower AV hardware costs due to a slower pace of deployment, and sustained discipline in operating expenses. We ended Q1 with cash, cash equivalents, and marketable securities of $90 million.

Today, we further reinforced our liquidity position with a successful common stock financing from existing and new investors, raising $100 million of gross proceeds. After fees and expenses, net proceeds are approximately $95 million. On a pro forma basis, this brings our Q1 cash, cash equivalents, and marketable securities to approximately $185 million. The successful financing strengthens our balance sheet and extends our liquidity into 2027. In summary, Q1 reflects a strong start to 2026. We delivered solid revenue growth, continued scaling of driverless deployments, and outperformed our free cash flow expectations while improving our full-year free cash flow outlook.

We believe that we are well positioned to scale our business, progress towards profitability, and generate free cash flow over time. We will now open the call for questions.

Operator: And your first question comes from Andres Sheppard-Slinger with Cantor Fitzgerald. Please go ahead.

Andres Sheppard-Slinger: Hey, everyone. Good afternoon, and congratulations on all the great progress and on the capital raise. Lots to unpack, so kudos to everyone. Don, I was wondering if you can give us a little bit of cadence in terms of how we should think about deployments for this year. Surajit, I think you alluded to Q2 and what to expect. How should we think about those deployments ramping up in the second half and maybe through next year?

Don Burnette: Thanks, Andres. As we said in the remarks, we expect the second half of 2026 to look very similar to the first half in terms of raw numbers, and we do expect the ramp of the trucks to accelerate quarter over quarter through 2027.

Andres Sheppard-Slinger: Got it. Very helpful. And can you expand a little bit further on Canada? What kind of opportunities do you look forward to there, and maybe remind us what the regulatory environment is for those that are not as familiar?

Don Burnette: Sure. This is a really exciting development for us. As we have been talking about for some time, we see our industrial and unstructured driving applications as being manyfold. You have the oil and gas industry, of course, which we have talked about at length. There is mineral and resource mining in many other countries, and then there is forestry and logging in the Pacific Northwest, both here in the U.S. and Canada and beyond. We are excited to announce West Fraser as a pilot opportunity that we will execute in Q3.

These are very difficult, unstructured, remote locations, which have a lot of the same challenges that you will find in some of the other applications that we have already been pursuing, including in the Permian. As it relates to the regulatory framework, this is something that we are working on currently. We will be operating initially on private land in Canada, which allows us to deploy driverlessly without anybody in the cab independent of the regulatory framework. We continue to work with regulators at the province level and at the national level in Canada to ensure a free and clear path to deploy driverless trucks at scale beyond those environments.

That is a development that we are working on, and we expect to have progress over time.

Operator: Your next question comes from the line of Analyst with Oppenheimer. Please go ahead.

Analyst: Thanks so much. Could you talk about the dexterity you have in terms of managing autonomy across multiple form factors? It looks like you will be able to deal with multiple types of vehicles in different environments. How quickly can that capability be put out into the field?

Don Burnette: We have held the belief for a long time that generalized AI is always going to win out over specialized implementations. From the very beginning, we wanted to be platform-agnostic and adaptable to many different form factors, not just makes and models of a vehicle, but also additional form factors. You are seeing the fruits of that labor as we deploy into the defense space with tracked vehicles and various form factors there, large trucks like you see on the highways, heavy-duty trucks that we implement in our unstructured environments like the Permian, and also logging trucks, which are slightly different themselves. Kodiak AI, Inc. Common Stock implements a single AI system behind all of these different products and applications.

The core underlying software that runs on these vehicles is actually the same across each one of them. That allows us to leverage the learnings, the data, the training, and all of the development costs across each of those verticals without having specialized teams or specialized AI or specialized training for each. The more experience we gain as a company, and the more that the Kodiak AI, Inc. Common Stock driver gains as a system, the stronger the AI becomes and the more utility we get across all the different verticals and applications we supply to our customers.

Analyst: That is helpful. And on the partnership with Bosch, you are working closely with them, but there has been an evolution in perception solutions. What is your capacity to integrate some of those innovations and monetize them, particularly around LiDAR and other sensors, and how much efficiency might you get?

Don Burnette: We are always evaluating new sensors. We use LiDAR, cameras, and radars in our system today, and we feel that sensor stack is the appropriate balance of cost and performance. You can always add more sensors to your system, which makes it more expensive. In our business, we can absorb a more expensive hardware solution that increases the safety and utility of the system. We continuously evaluate products on the market from providers both in the U.S. and abroad, across LiDAR, radar, and camera. We demonstrated at the ACT Expo in Las Vegas with Bosch a concept of the next generation of our SensorPod, which includes Bosch's in-house radar and camera sensors.

We are excited to continue to develop a more mature, reliable, and scalable system with Bosch as our tier-one supplier.

Operator: Your next question comes from the line of Itay Michaeli with TD Cowen. Please go ahead.

Itay Michaeli: Thanks. Hi, everybody. Maybe to continue on the last question with Bosch, can you size how you see the cost-cutting opportunity in the second generation versus where we are today? I think I also heard a mention around Q2 investments for hardware cost improvement. Can you elaborate?

Don Burnette: Sure. There are a couple of factors that go into reducing the cost of your system. You can engineer it to be cheaper, you can drive scale and volume, which reduces the cost of components, and you can optimize manufacturing processes as you scale into higher quantities. From the engineering perspective, we are putting R&D resources behind driving down the BOM cost, which is a main driver of COGS for our solution, and we expect to start to see those costs come into effect in the next several quarters.

Surajit Datta: To add to what Don mentioned, for us it is a three-pronged approach. First, design enhancements—we are starting to undertake these and there will be some NRE spend in Q2 as we referred to on the call. That goes on the sensor side and on redundant systems; those are areas we are working on. Second, increasing the scale of production with Bosch and Rausch—Rausch able to provide high-quality assembly and Bosch able to provide high-scale assembly across our hardware. We expect that to drive cost optimization over time. Lastly, we are enhancing a global supply chain organization. As we scale, we should be able to procure more effectively, and that will drive down costs.

The strength of our system is to be hardware-source agnostic, which allows us to be much more efficient on cost over time.

Itay Michaeli: That is very helpful. As a follow-up, with the announcements with West Fraser and some defense wins, as you look out a couple of years, how would you rank these opportunities in terms of impact on the company?

Don Burnette: It will shift over time. Defense is a bit of a wildcard because it is difficult to predict the timing of contracts and spend. As mentioned in the remarks, we are excited about what we are seeing in the FY2027 budget, with billions of dollars put toward autonomous vehicle efforts within the Department of Defense. That level of funding has not been seen in the past, so we are optimistic there will be tailwinds for us to take advantage of in the next 12 to 24 months, and we expect that to contribute meaningfully.

At the same time, we are growing our industrial business today, both with Atlas and by bringing on additional customers such as West Fraser, so we see steady growth in that industry. The long-haul opportunity is certainly the largest by a significant margin relative to the other areas. As we prove out the safety case, close out our ARM at 100%, deploy the driverless highway product, and start to deploy trucks into customer fleets, we think that ultimately long-haul will be the largest contributor down the line to our revenues and growth. The exact transition point is hard to pinpoint, but it will be in the next couple of years.

Operator: Your next question comes from the line of James McIlree with Chardan. Please go ahead.

James McIlree: Thank you, and good afternoon. The deal with Rail Transport, is that on your trucks or their own trucks, and is there an observer in the cab at least initially?

Don Burnette: Today it is with our trucks, similar to the way we operate with other carriers. We offer transportation-as-a-service to third-party fleets and move freight on their behalf as a third-party capacity provider, and we will work with Rail in the same capacity that we do with other trucking carriers and trucking companies we work with. And yes, there is an observer behind the wheel for now.

James McIlree: Great, thank you. Can you address product migration, particularly with your collaboration with NVIDIA?

Don Burnette: We have been a customer of NVIDIA for a long time, as most of the industry has, and we have been working closely with them on development of their latest products. We are excited about the Thor platform that will be in the next generation of our product. NVIDIA DRIVE Hyperion is an ecosystem of components you can put together to build a fully reliable, automotive-grade autonomy compute system. We are working closely not only with NVIDIA, but also with tier-one suppliers to build that into the next-generation system that we can build at scale.

We continue to be excited to work with them and about what they are bringing into the future of low-power compute for applications such as self-driving trucks.

James McIlree: Does this $100 million get you to cash flow breakeven?

Surajit Datta: As mentioned during the prepared remarks, this provides us liquidity into 2027. We will continue to be opportunistic about additional capital raises, and we expect to become S-3 eligible, which provides us with additional flexibility in accessing capital markets. This $100 million has come from both existing investors, including Ares, who was a SPAC sponsor, and new investors. We believe this demonstrates confidence in our strategy, execution, and the long-term opportunity. We expect to get access to additional capital as needed to get to breakeven.

Operator: Thanks, Jim. Your next question comes from the line of Analyst with Morgan Stanley. Please go ahead.

Analyst: Great, thanks for taking my questions. On the defense opportunity, who is your competitor there, if you have any at the moment? And what do you know about the program so far—is it just the amount in the defense budget, or do you know if there will be an RFP, the size of the program, or specs?

Don Burnette: In terms of competitors, there is a long list of companies that play in the defense space. Prominent ones include Forterra and Overland AI, which have been established in this space. What Kodiak AI, Inc. Common Stock brings uniquely to the table is a commercially mature technology stack. We have actual driverless deployments in the hands of customers today, and we understand how to build safe and reliable systems that we can bring to military use cases to help save lives on the front line. Regarding the program, the budget is not specific to one program or one RFP. We are already working with General Dynamics Land Systems to bid on future programs.

It is great to have a partner like them to take this technology to a more mature and credible level. We will continue to work with them on new RFPs, contracts, and programs as they come about. The budget underpins a number of programs that exist today and are being conceived and created in the near and long-term future.

Analyst: Got it, that is helpful. As a follow-up, on Atlas and the new OEM, can you unpack that decision? Was that at their request or your request, and why the change? Is it just the cab configuration or something else?

Don Burnette: There are many factors. The cab configuration is one, as mentioned in the remarks. Generally, fleets and trucking companies like to diversify their fleets rather than be single-platform. The request came from the Atlas team, and we are excited to support the bring-up of a new platform—not only to help support their goals of rolling out autonomy at scale, but also to prove out the modularity and adaptability of our system on other platforms and to establish close relationships with additional OEMs. Bringing up a new OEM is a win-win, and it is also a make and model that we can bring to other customers and jurisdictions. It gives customers more flexibility and optionality. It shows Kodiak AI, Inc.

Common Stock is ready to scale and be flexible to meet the customer where it is.

Operator: Your next question comes from the line of Walter Piecyk with LightShed. Please go ahead.

Walter Piecyk: Thanks. Can we get some more specific terms on the $100 million and why you elected to do a PIPE with warrants? I know Aurora used an ATM. What other things did you look at in terms of cost of capital, and can we get the terms of the $100 million?

Surajit Datta: Happy to, Walter. Our priority was to secure committed capital from high-quality investors with speed and certainty. This helps strengthen our balance sheet to support our growth plans and enhance our liquidity, and it gets us liquidity into 2027. Transactions of this nature are typically priced at a discount. We believe these terms reflect market conditions, the range we are seeing for similar transactions, and the strategic value of capital that provides extended liquidity. At a high level, the transaction raised $100 million in gross proceeds. The issuance price was $6.50, and we issued warrants along with that. We will have more details in our recently filed 8-K and the upcoming 10-Q. The warrants are priced at $6.00.

Walter Piecyk: Was there an alternative source of capital that was less dilutive? The stock is at $9 now, and you had a lot of announcements today. What alternatives did you look at?

Surajit Datta: We always look for opportunistic financing. We will have more options available as we expect to become S-3 eligible, which will give us additional options on financing.

Walter Piecyk: What was the reason for the timing now as opposed to waiting until the end of Q3?

Surajit Datta: We had announced that we had liquidity into 2026. This gets us approximately an additional six months of liquidity.

Don Burnette: I would also note that ATMs are not available before you are S-3 eligible, so that is not available to Kodiak AI, Inc. Common Stock at this time.

Walter Piecyk: Understood. Thanks. On the operational side, on flatbeds and loggers, you are pitching a modular approach. When other autonomy companies come out with a new vehicle, there is a period of learning for the new vehicle. How does your process differ? Different types of loads have different dynamics—how does that work with your driver in terms of new vehicle, different type of load, and what you have to do to make that work?

Don Burnette: We have continuously expanded and pushed the limits of what the system is capable of doing. In our last call, we talked about expansion into double and triple trailers. Triple trailers are incredibly complicated, with a small margin for error and many dynamical challenges, especially at heavy loads like the 275,000 pounds that we are pulling. The Kodiak AI, Inc. Common Stock driver has learned how to handle various distributions of load, from single trailers that are partially filled to triple trailers that are fully filled. The dynamics are different, but the system understands those dynamics. We see logging as a natural extension of what we are doing in the Permian. It will be a single trailer to start.

Logs are strapped down tightly, as is the sand in the trailer, so it is not a dramatic difference. All of our training data—from multiple sources, both structured environments like highways and surface streets and unstructured environments like what we find in the Permian, in Alberta, and in our military testing at various sites around the country—is brought together along with generative AI techniques that allow us to style transfer other types of data we may not be able to collect directly into a single AI system that we then deploy across the fleet.

It is the same software that runs across our Permian application for trucks owned by Atlas and ultimately the trucks that will be owned and operated by West Fraser. There is definitely testing and validation with every platform, but it is one software stack across platforms.

Operator: Ladies and gentlemen, that concludes our question and answer session. Thank you all for joining. You may now disconnect.

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