This conference call transcript was computer generated and almost certianly contains errors. This transcript is provided for information purposes only.EarningsCall, LLC makes no representation about the accuracy of the aforementioned transcript, and you are cautioned not to place undue reliance on the information provided by the transcript.
spk05: Good day and thank you for standing by. Welcome to the Q3 2023 Sarcos Technology and Robotics Corporation Earnings Conference Call. At this time, all participants are in a listen-only mode. After the speaker's presentation, there will be a question and answer session. To ask a question during the session, you will need to press star 1 1 on your telephone. You will then hear an automated message advising your hand is raised. To draw your question, please press star 1 1 again. Please be advised that today's conference is being recorded. I would now like to hand the conference over to your speaker today, Julie Kegley with Financial Profiles for Sarcos. Please go ahead.
spk01: Thank you, Operator. Good afternoon, everyone, and welcome to the Sarcos Technology and Robotics Corporation third quarter 2023 earnings call. Joining us on the call this afternoon are SARCO's President and Chief Executive Officer Laura Peterson and Chief Financial Officer Drew Hamer. Laura will start the call with a discussion of business highlights from the third quarter and recent events, and Drew will then talk in more detail about the financial results before they take analyst questions. Before we begin, we must state that today's call will contain forward-looking statements, including statements concerning future commercial production, release, and availability of our products, product usage, features, capabilities, and value proposition, target markets and market trends, size, and expectations, strategic direction, company facilities, customer demand, and future financial results, conditions, and cash flows, including future costs and cost trends, cash usage, restructuring charges, and liquidity. These statements represent management's belief and expectations as to future events as of today, but there are many risks and uncertainties that could cause actual results to differ from what we have projected. Among those risks and uncertainties are those described in our report on Form 10-Q filed today with the SEC, and those mentioned in today's earnings press release, both of which are available on the SEC's website and in the investor section of our website at starcoast.com. We encourage you to review the risks and uncertainties described in the press release and 10-Q and in our other filings with the SEC for further information regarding these actual potential risks and uncertainties. We also encourage you to review the special notes regarding forward-looking statements included in the earnings release and 10-Q. In addition, we will be discussing certain non-GAAP financial measures on our call today. Throughout this call, all financial measures will be GAAP unless otherwise noted. A reconciliation of any non-GAAP measures to the most directly comparable GAAP measures, as well as the descriptions, limitations, and rationale for such measures are included in the earnings release. A recording of this call will be available on our website until December 14, 2023. The information that we're giving on the call is as of today's date, and we undertake no obligation to update the information subsequently, except as may be required by law. Now I would like to turn the call over to Laura Peterson, President and CEO of SARCOS. Laura?
spk00: Thank you, Julie, and good afternoon to all of you joining us on today's call. I am pleased to be speaking to you as the recently appointed President and CEO of SARCOS, a role for which I am sure many of you remember I said I was not a candidate. However, much has changed in a short time, and I was honored to be asked by the Board to accept the permanent role. As I began leading the company in May, it was apparent that we needed to focus the business on clearly defined end markets. With 18 products and solutions, we did not have the capacity to commercialize each one of those with our available resources. It was important that we rigorously prioritize our products. After significant analysis, we identified subsea, aviation, solar and software, as the four markets with the most potential for near-term revenue growth and acute customer need and the greatest traction in evolving markets. We defined the products and product concepts for those end markets, initially narrowing 18 product areas to four. But our work did not stop there. We continued our rigorous, data-driven review of our products and development programs leading to a deeper understanding of the risks and work necessary to bring all of these products to market. With the consideration of our cash position, as well as third party dependencies, customer decision timing, and the cost and time to achieve a significant and steady revenue stream from our hardware products, it was clear that we should adjust course rapidly to right size the company and get our cash usage down to a level that we believe will provide the best opportunity for success with our available resources. We made the decision to suspend our hardware commercialization efforts, implement a significant reduction in force, and focus our resources on our AI platform. We believe this is the right thing to do. The common key differentiator of our robotic systems has been our advanced software including our performance-enhancing artificial intelligence and machine learning capabilities. We believe that there is a significant near and midterm market need and customer value proposition for the capabilities our software platform will provide. Our AI ML software platform is being developed to greatly reduce the time to program and train robotic systems, which we believe will accelerate implementation to a small fraction of the current approach providing customers with significant increased productivity at a lower cost and in a more efficient manner. By design, the success-based learning approach used by our software will enable robotic systems to perceive their environment and quickly adapt to changing circumstances by generalizing from their past experience. This ability to continually learn and apply their learnings to new situations and challenges will enable these robotic systems to quickly adapt and continue to perform the desired task. We believe that our AI software platform, which is applicable to the majority of the industrial robots being sold around the world, will enable a dramatic reduction in robotic training times while also making industrial robots far more agile, meaning they can perform more tasks with greater variability. similar to how humans can perform a wide variety of tasks. In our lab environment, we have trained robotic arms to do simple tasks in minutes. Our software platform enables the robots to learn how to work around unforeseen changes or obstacles by building on their initial programming. The robots incorporate internal and external environmental inputs that allow them to understand their environment, determine reasonable behavior in unforeseen situations, and quickly apply them to the task at hand. Each newly learned task will then be incorporated and used to perform future tasks. This closed-loop autonomy approach is the key to how our software will help reduce costly workflow stoppages and prevent unnecessary downtime. We expect to bring the product to market in the first half of 2024, with revenue being recognized beginning in the second half of 2024. Our decision to suspend commercialization efforts of our hardware products and focus on our software platform will result in significant cash savings and increased efficiencies throughout the organization, in large part by drastically reducing headcount. We will continue some hardware system R&D efforts on a substantially reduced scale in part to support our software platform development efforts. We will be closing our Pittsburgh facilities as well. We are confident about the future of our advanced software and technology focus and see tremendous potential for a SaaS business. By decoupling our advanced AI ML software from our own robotic systems, we believe we have the opportunity to reach a much broader market more quickly by targeting existing deployed robotic systems and new sales of third-party systems. We can provide customers with the solutions they need through the intellectual capital that Sarkos brings to the table, but without requiring significant investment in hardware development and production. One of the reasons I am confident in taking the path of a SAS model company is the advanced state of our AI ML program that began in 2017 with a vision to use these technologies to greatly enhance the capabilities of our robotic systems. We progressed to our first CITAR government proposal, which stands for Cybernetic Training for Autonomous Robots, in 2019. We began significant development work in 2020 when we hired Dr. Denis Gorachek, our Chief Technology Officer, who heads our AI ML software development efforts. With more than 25 years of experience in the AI and ML technology space, Dennis is an internationally recognized leader who has written more than 40 academic papers and holds several patents in applied controls for autonomous robotics and machine learning. With years of Department of Defense funded AI software development programs under our belt, as well as ongoing DOD funded contracts, and one of the foremost authorities in the field leading our technology vision, we are well positioned to excel in redefining the use of software in the programming, training, and management of industrial and other advanced robots in complex and dynamic environments. Throughout this time of organizational change, we have continued to build momentum through customer wins. In addition to the expanded AI contract with the Air Force Research Laboratory that I mentioned last quarter, we recently reported an additional important achievement. We received a $13.8 million four-year contract from the U.S. Air Force to advance artificial intelligence and machine learning software. The contract supports the development, integration, and validation of our AI and ML software framework for success-based learning, which will allow robots to perceive their environment, determine reasonable behavior in unforeseen situations, and quickly change their actions. We are striving to teach robots to emulate what humans do to adapt to new situations, leverage existing knowledge, and then generalize from limited data to fill in the gaps. Our goal is to outperform current AI approaches in both effectiveness and efficiency to create greater synergy between human workers and AI technology to enhance productivity and workflow agility. We believe we offer a compelling and differentiated value proposition with our software. It has been and will continue to be tested on both existing third-party robotic platforms as well as Sarkoz's own development platforms to mitigate risks associated with deploying our advanced software in a commercial setting. As we move forward, Ben Wolfe, founder, board member, and former CEO of the company, has rejoined the executive team as executive vice chairman. I asked Ben to be a part of my team to leverage his extensive experience with the company, potential customers, and the industries and markets we are targeting. He will support our efforts to bring our AI software platform to market, as well as help evaluate and pursue strategic business opportunities, support our commercialization efforts, improve speed to market, and accelerate revenue. Ben and I, along with the rest of the board, are united in our belief that robotic AI and ML software is the future for Sarkov. AI and ML aren't shiny new objects or buzzwords for us. They are an integral part of the years of work and millions of dollars we've invested. And we see potential applications in the majority of the robotic arms being sold in the market today. I am pleased with the progress the team has made. And I am optimistic about our future as we move forward to serve customers with our robotics AI ML software platform. I'll now turn the call over to Drew to report on the financials.
spk02: Thank you, Laura. To everyone on the line, it is a pleasure to be here today speaking with you. As I review our financial results today, all comparisons I will use are year over year. For the third quarter of 2023, revenue was $1.8 million compared to $4.7 million during the third quarter of 2022. The lower revenue in Q3 was primarily due to the completion of certain product development contracts during 2023 that had not yet been replaced with new contracts, offset slightly by an increase in product revenue related to the sale of two Guardian C-Class units. Cost of revenue decreased to $1.2 million in Q3 2023 as compared to $3.6 million in Q3 2022, mainly due to decreased labor and material expenses charged to product development contracts during the quarter. Third quarter 2023 total operating expenses, including costs of revenues, were $32.6 million, an increase from the third quarter 2022 operating expenses, $31.9 million. I'll now discuss the operating expenses in more detail. In connection with the July and November restructurings as previously announced, The company incurred charges of $11.2 million in the third quarter of 2023, including $5.5 million in employee and employee-related charges, $5.2 million for the write-down of inventory, and half a million dollars related to the impairment of certain fixed assets. Research and development expenses were $10 million in the third quarter, down slightly from $10.5 million in the third quarter of 2022. This decrease was driven primarily by reduced 30-party professional service expenses during the current year period as part of our prioritization efforts on development and commercialization of our focused products. General and administrative expenses were down 48% to $7.6 million in the third quarter, primarily due to reduced stock-based compensation expense of $6.8 million due to certain awards vesting in the prior year, and reduced outstanding unvested awards due to employee terminations during the current year period. Sales and marketing expenses were $1.8 million, a decrease of 27% compared to the third quarter of 2022 due to a decrease in professional service fees related to third-party platform expenses utilized in data management of our products and services. Third quarter 2023 net loss was $29 million, or a loss of $1.13 per share, compared to a net loss of $22.5 million, or a loss of 89 cents per share in the third quarter of the prior year. Third quarter non-GAAP net loss was $17 million, or a non-GAAP loss of 66 cents per share, compared to a non-GAAP net loss of $18.6 million, or non-GAAP loss of 74 cents per share in 2022. Please note, on July 5th, we affected a one-for-six reverse stock split of the company's outstanding shares of common stock. All share and per share amounts have been retroactively adjusted for all periods presented to reflect the reverse stock split. We ended the quarter with $55.1 million in unrestricted cash, cash equivalent, and marketable securities. I am now going to turn to our financial guidance for the fourth quarter of 2023. As Laura discussed, and I hope you saw in our other announcements today, we are pivoting the business to focus on the larger opportunity of a robotic artificial intelligence or AI and machine learning or ML software platform. With the need to ensure we have sufficient financial resources to pursue that opportunity, we have made the difficult decision to suspend for the foreseeable future our subsea, aviation, and solar robotics hardware commercial efforts. Some small R&D hardware efforts will continue, in part to support our software platform development efforts. However, we intend to address these markets through our AI ML software platform. As a result of the decision to streamline our business, approximately 150 employees were notified today that their positions in the company will be eliminated on January 16th of 2024. This will leave approximately 65 employees in the company, which we currently expect will be the approximate headcount throughout most of 2024. We anticipate incurring additional restructuring expenses related to restructuring actions taken during 2023 in the range of $22 million to $24 million during the fourth quarter of 2023 and the first quarter of 2024. These expenses include approximately $4 million in personnel expenses such as salaries, wages, benefits, and severance related to the eliminated headcount. The remainder will be non-cash expenses related to expected accelerated amortization of intangible and other assets due to the strategic shift initiated during the fourth quarter. Due to many variables associated with the organizational and business changes announced today, I will not be providing revenue guidance for the fourth quarter. I can't tell you that we expect our cash to be approximately $39 million at the end of the fourth quarter. Cash usage from ongoing operations should average approximately $1.6 million per month in 2024. With the launch of the software platform in the second half of the year, The cash usage could be reduced further by customer purchases of the service. Reflecting our new business model, quarterly research and development expenses are expected to decrease in the first quarter of 2024 by approximately 80% when compared to the third quarter of 2023. After adjusting for stock-based compensation expense, we also expect the implementation of our business realignment will result in general and administrative expenses trending down on a quarterly basis for the next two quarters. We expect general and administrative expenses for the first quarter of 2024 will decrease by approximately 35% when compared to the third quarter of 2023. Our SaaS business model is expected to result in sales and marketing decreasing by approximately 60% in the first quarter of 2024 from what it was in the third quarter of 2023. Looking at our balance sheet, we are significantly reducing our cash usage to provide us the runway to continue developing our AI ML software platform to capitalize on anticipated demand. We intend to manage our average monthly cash usage to approximately $1.6 million in 2024. We believe that we have sufficient liquidity to operate well into 2025 without additional financing. In conclusion, by running a leaner business that is more efficient in reducing cash usage, the company is in a stronger position to reach profitability. We believe this should lead to long-term stockholder value creation. Now, I'd like to turn the call over to the operator. Operator, would you kindly repeat the instructions to ask a question?
spk05: As a reminder, to ask a question, please press star 1-1 on your telephone and wait for your name to be announced. To withdraw your question, please press star 1-1 again. Please stand by while we compile the Q&A roster. And our first question comes from Rob Mason with Baird. Your line is open.
spk04: Yes, good afternoon. Hi, Laura. Hi, Drake. Hi, Rob. What it is,
spk03: Just to touch real quick, just around your projected cash burn rate for next year, averaging $1.6 million a month, do you expect much volatility around that embedded in that estimate?
spk02: No. The only volatility I'd anticipate around that is if the sales come in faster than we thought. Right now, that's mostly just the cost of getting the platform up and running. And then as sales start to materialize, they might bring that use down.
spk03: Okay. So the presumption would be once we get past mid-January, say, you know, you should roughly be at that level.
spk02: That's right. When all the alignments of the teams will get down to the 65 people that we were talking about in the press release, that's right. Sure.
spk03: Okay. You can just elaborate a little bit on, you know, this effort, you know, pivoting to the software model, but your channels to market, how you plan to, you know, once it's ready to be commercialized, take to market? in the first half of next year? Is this going to be more of a direct model or do you envision some indirect channels to market?
spk02: The expectation is you launch the new service that it will primarily be the direct model. We have a lot of very strong relationships with existing customers on the commercial side and on the government side. And we anticipate being able to enhance those with this new solution. And you will use them for at least for the early days of selling the solution. And then as we move forward, then we'll consider other channels as they present themselves.
spk03: Just as a follow-up on that, should I envision, as you take this out to existing robotics players, are we mainly talking about traditional robotics? Are these collaborative robotics? Is there a bias one way or another where you think you can find value easier to be realized early on?
spk02: So the beauty of the software as it's been developed is that it allows people to train their arms. As we mentioned, we've done it in the lab in a couple of minutes, whereas now it could take potentially weeks or more to train a line and bring it up. And that is just the initial... product that would be available, then the real solutions, Robin, it's complicated, but the real solutions will allow the systems to train themselves. Sorry, give me one second. I'd like to give you some of the technical words. The platform enables the robots to learn how to work around unforeseen changes or obstacles by building on their initial programming. And the robots incorporate internal and external inputs that allow them to understand their environment, determine reasonable behavior in unforeseen situations, and quickly apply them to a task at hand. And then each newly learned task that the robot has trained itself to do will then be incorporated and used to perform future tasks. And then it goes to even more sophisticated environment and then does it in a closed-loop autonomy approach so that the software will help reduce costly workflow stoppages and prevent unnecessary downtimes for customers. So, you know, these are, you know, really strong reasons for us feeling confident about taking a path of a SaaS business model using this advanced state of our AIMO program that began in 2017. with a vision to use these technologies to greatly enhance the capabilities of the robotic systems we were developing. And I think as you're aware, if you look back kind of at our history, we progressed to this stage with our first CITAR government proposal in 2019, and then we were fortunate enough to have Dennis join the company in 2020, and he's been able to really refine the vision for the products and develop them to the state that they're at right now, and he will continue to head our AIML efforts And then so, you know, with this more than 40 years of experience and everything, you know, we're in a very good position to capitalize on this opportunity.
spk03: Sure. Just around, maybe last question, I'll hop back in the queue, but just around the business model itself, and how should we get comfortable on the ability to scale this relative to, you know, what is a, you know, price point? I guess it'll be sold on a per seat basis, per arm basis subscription, but is there any detail you can provide there?
spk02: Yeah, so there are a couple of things that'll enable the scaling of the solution. The first, the very simplest access point for one of our customers will be the ability to do it on a per arm basis. So they'll want to be able to train their arm in a few minutes, whereas right now it could take them weeks or months or longer. So they'll buy it on a per arm basis. And then there's all kinds of other modules in the system that they'll be able to utilize to take on the various tasks that I was just describing a moment ago. And those will be incremental upsells and cross-sells that we'll be able to provide to them so that they can take full advantage of the system to the extent that they need it without requiring it up front. So they can advance as they go through the various stages and start getting more sophisticated. When I talk about internal and external sources, it could be the camera that's around the various armor part of it, or it could be external cameras that are not even connected to the armor part of it. So the sophistication of the product and its interpretation of the information that's being generated will then be used by the robot and software to modify the behaviors of the robot for the various needs that customers have designed it for. So it'll be assessed. There'll be term licenses. There'll be a number of different modules that customers can buy into based upon their various needs and based on the various solutions that they're trying to put together. And it'll be available in a number of different forms so that we can ensure their success.
spk04: Sure. Thank you. Very good. Thank you.
spk05: As a reminder, to ask a question, please press star 1 1 on your phone. Again, that is star 1 1 on your phone. One moment, please. One more moment for our next question. And this concludes today's question and answer session. I would now like to turn the conference back to Laura Peterson for closing remarks.
spk00: Thank you. We are confident about the decision to focus on our AIML software and excited to build on the strong foundation that we've laid over many years as we shared in our earnings call today. Thank you for joining us and have a great evening.
spk05: This concludes today's conference call. Thank you for participating. You may now disconnect.
Disclaimer