Item 1. Business
Item 1. Business.
The following discussion should be read in conjunction with the information about us contained elsewhere in this Report, including the information set forth in our consolidated financial statements and the related notes. Some of the information contained in this section or set forth elsewhere in this Report, including information with respect to our plans and strategy for our business, includes forward-looking statements that involve risks and uncertainties. You should read Part I Item 1A Risk Factors and the section titled “Special Note Regarding Forward-Looking Statements” for a discussion of important factors that could cause actual results to differ materially from the results described in or implied by the forward-looking statements contained in the following discussion and throughout this Report. We use the terms “Sarcos,” “the Company,” “we,” “us,” and “our” to refer to Sarcos Technology and Robotics Corporation.
Overview
Our mission is to deliver software to our customers that enhances the utility and functionality of third-party stationary and mobile robotic systems by enabling these systems to quickly observe, learn, reason and act in structured and unstructured environments. Our AI/ML Software Platform is being designed with artificial intelligence (AI) and machine learning (ML) techniques to enable robotic systems to perceive their environment and quickly adapt to changing circumstances by generalizing (i.e., learning) from their past experience using dynamic real-time operations “on the edge” (i.e., on the robotic system) without extensive programming and with minimal robot training. We believe this “human-like” ability to learn and adapt will be a key differentiator in helping our customers maintain optimal productivity in dynamic or unstructured environments, where new situations and unexpected challenges are more likely to cause delays and costly downtime. Our value proposition is further enhanced relative to other competitive solutions because robotic systems using our AI/ML Software Platform are not required to be continuously connected to the cloud for our software to function, thereby reducing the performance issues associated with poor connectivity and latency typically associated with processing in the cloud. Our approach also reduces the expense typically associated with transmitting large amounts of data to and from the cloud.
As a pioneer in the robotic systems industry, we benefit from both experiences and lessons gained from our 30-plus years, as well as significant investment in our internal research and development efforts. Software has been an integral part of our development efforts over the years. Our vision for our AI/ML Software Platform began in 2017 as a foundational technology to enhance training for the autonomous operation of our own internally developed hardware solutions and progressed to our first CYTAR (Cybernetic Training for Autonomous Robots) government project in 2019. Significant design and development work began in 2020 when our Chief Technology Officer, Dr. Denis Garagic, joined our team. We have since continued to develop our AI/ML software both for the U.S. Department of Defense and in connection with our development of commercial robotic systems. As previously disclosed, in November 2023, we decided to suspend our hardware product development efforts to focus on commercializing our AI/ML Software Platform, although some de minimis hardware-related research and development efforts continue. By de-coupling our AI/ML Software Platform from our own hardware systems and applying it to a wide range of third-party robotics systems, from industrial robots and cobots to mobile systems potentially including drones, autonomous mobile robots (AMR), autonomous underwater vehicles (AUV) and remotely operated vehicles (ROV), we believe we can reach a much broader market more quickly and better utilize our remaining cash resources.
We are designing our AI/ML Software Platform to be hardware agnostic in order to be compatible with most industrial robots being sold today and to support other specific types of commercially available robots with additional development and the necessary application programming interface (API). The AI/ML Software Platform is expected to enable robotic systems to perform tasks that involve variations in the environment and the objects being manipulated by the robot. Specifically, we expect our AI/ML Software Platform to incorporate internal and external environmental inputs that allow robots to comprehend their environment, determine reasonable behavior given these inputs and to act in real time to achieve the expected task. Each newly learned task will then be incorporated and used to perform future tasks. We believe this closed-loop autonomy approach is the key to how our software can expedite robot training, expand the tasks that a robot can perform, reduce costly workflow stoppages, mitigate downtimes and reduce human labor requirements.
A variety of industries ranging from manufacturing to warehousing encounter lengthy and costly efforts to program, manage, and modify their robotic systems. These industries also experience significant limitations with the tasks that existing robotic platforms can perform, resulting in more human labor required and a lower return on investment from robotic system deployments than what we believe will be possible when our software is deployed on these machines. We are designing our AI/ML Software Platform to enable industrial robotic systems to function with human-like reasoning through flexible and adaptable learning capabilities such that an industrial robot can perform a variety of tasks without the need for costly
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reprogramming efforts. We believe that the AI/ML Software Platform will enable autonomous functionality to address challenging and dynamic environments for industries that can benefit from a high degree of adaptability and efficiency.
Industry Background
Robots have been commercially available and used in industrial and manufacturing automation for many decades. These industrial robots are typically large, stationary robotic arms designed to automate repetitive tasks in a controlled environment (e.g., a factory assembly line) that require consistency, speed and strength greater than what a human can accomplish. Industrial robots generally execute plans by rote programming (functions that are programmed in advance by a human engineer). Over time, industrial robots have become more sophisticated and are now widely adopted in a host of applications and across many industries. While this kind of automation brings significant benefits to industrial and manufacturing efforts, it also has its limitations. For example, these robots are typically deployed in controlled settings, fixed in place, used to accomplish a single repetitive task and not easily reprogrammed without costly and time-consuming retraining.
In the industrial and manufacturing automation space, productivity and cost-effectiveness depend greatly on avoiding downtimes. Downtime can be caused by many factors, but we believe the most significant are due to programming and reprogramming of robotic systems, disruptions to the controlled environment, whether due to physical obstacles or imprecise positioning, and the need to implement production change-overs. Initial programming or reprogramming of robotic systems is a costly and time-intensive task, requiring highly skilled programmers. We understand from early customer engagement that reprogramming a single robotic arm can take weeks to months in some cases. Reprogramming thousands of robotic arms on a full assembly line to build a different product or accommodate a new component is therefore costly and can put the line out of commission for a significant period of time, reducing or delaying production and sales. Further, many industrial or manufacturing robotic systems deployed today are not designed to perform tasks in dynamic or unstructured environments. As a result, a change or disruption in the environment, such as the insertion of an obstacle or the imprecise placement of parts, can result in the system shutting down until human assistance resolves the situation, resulting in additional costs and lost production.
Recent efforts to use AI technologies to address issues such as changing and dynamic environments typically depend on access to enormous databases with large language models (LLMs) residing in the cloud and using enormous amounts of real-world robotic data sets collected over time. In these cases, training occurs by connecting to these databases, doing extensive searching to try to find case-applicable data and models and then attempting to use the new data to recommend a viable solution. This process requires persistent cloud connectivity, driving increased costs, and is time-consuming, significantly reducing the benefits of these AI technologies.
Our Solution
We are designing our AI/ML Software Platform to enable industrial and manufacturing robots, such as robotic arms to:
• be programmed and reprogrammed quickly with training capable of occurring experientially through teleoperation in as little as a few examples taking only a few minutes;
• observe and assess their environment with our perception functionality that enables robots to distinguish between components essential to their tasks, obstacles to be avoided and irrelevant externalities without the need to connect to LLMs and extensive cloud-based databases;
• learn to recognize and manipulate different objects to accomplish planned tasks quickly and precisely, even in dynamic or unstructured environments, requiring far less training data than traditional AI models;
• quickly reason and determine how to accomplish the desired task in a stable, safe, and controlled manner in the face of obstacles or other unexpected environmental changes;
• make real-time, AI-enabled decisions on the edge without the need to maintain connectivity to the cloud, eliminating the cost and latency associated with cloud-based AI computing; and
• work with most industrial robots being sold today.
To accomplish this, we are incorporating our proprietary full stack, closed-loop autonomy technology into our AI/ML Software Platform that operates on the edge, enabling robotic systems to observe, learn, reason and act in real-time without the need to connect to the cloud to try to find an applicable LLM. Unlike LLMs, which are generally used to predict an outcome and make
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a recommendation, our AI methods are designed to enable a robot to make real-time decisions and act while using much less data and taking much less time. In many instances, we believe our solution will be significantly more data-efficient as compared to deep learning-based methods due to its ability to make decisions with just hundreds of parameters rather than billions.
We aim to address current challenges in automation by developing a software platform that:
• enables humans to intuitively re-train a robot to perform a different task quickly thereby reducing costly delays resulting from the need to reprogram assembly lines;
• enables robots to be capable of dynamic reasoning such that the robot can work around a physical obstacle or dynamically adjust its orientation to achieve the task, thereby reducing the need to reprogram robots and incur costly delays; and
• operates “on the edge” without the expense or delay of having to connect to the cloud to exhibit human-like reasoning in real time.
The AI/ML Software Platform’s ability to operate “on the edge” is a key differentiator because, without the need to use large amounts of cloud-based computing, our AI/ML Software Platform can efficiently operate autonomously in dynamic environments while reacting to new circumstances without the need to access new data sets or be reprogrammed or retrained. In addition, our AI/ML Software Platform is being designed to fuse multi-sensor data inputs together to improve system situational awareness, increasing its flexibility and adaptability. We expect other important future capabilities to include solving for system stability and automated end-effector orientation to match the target object, enhanced computational efficiencies achieved through the use of our domain-specific language models and the use of dynamic model inference methods to generalize with only a few demonstrations.
Because our AI/ML Software Platform is being designed to work with most industrial robots being sold today, we expect that our AI/ML Software Platform can benefit a wide variety of industries such as industrial manufacturing, warehousing and logistics, defense, infrastructure maintenance and repair, energy and aerospace and aviation, among others. Based on product testing and trials, we expect our AI/ML Software Platform to greatly increase productivity across a variety of use-cases, while significantly reducing associated costs of programming and deploying these systems.
The AI/ML Software Platform
Artificial Intelligence & Machine Learning
We are designing our AI/ML Software Platform to enable robots to be capable of human-like reasoning in their ability to learn multiple tasks and efficiently manage disruptions or obstacles. Once initial training/programming occurs, our closed-loop autonomy is expected to enable the robot to adapt to changes in its environment without human intervention or reprogramming. After minimal initial training, robots using our AI/ML Software Platform are expected to operate in a closed-loop to continuously observe, learn, reason and act so that they can adapt and continue to complete the desired tasks in the face of a changing environment.
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We are designing our AI/ML Software Platform to enable robots to:
1. Observe: Using a variety of sensors (e.g., vision, LiDAR, radar and acoustic) to perceive a dynamic and unstructured environment with situational awareness.
2. Learn: Typically learn a task in approximately one to five human-controlled demonstrations via a variety of methods including, remote manipulation, virtual reality manipulation or natural language instruction. We believe our dynamic reasoning model will require much less training data than traditional models. Using this learning data, the AI/ML Software Platform is expected to create a mathematical model of the data and store it in the platform as a task. The model is then updated over time as more data is obtained. Over time, each robot will create its own library of tasks (a “Task Library”). By operating “on the edge” and not accessing external large data sets, the learning process can happen faster and cheaper and without the need for a connection to the cloud.
3. Reason: Reason using probabilistic ML techniques, in a similar manner to human logic, when an unexpected or unknown event occurs. The robot would rely on its Task Library as a starting point and then infer to adjust to circumstances in real time.
4. Act: Applies human-like logic and adapts its task model in real-time to translate observations into a control message that adjusts the behavior in a safe and controlled manner to complete the task. For example, in our testing lab an arm robot has continued the task of sorting items by color even after an obstacle was placed in its way. As a result, we expect there will be no need to shut-down production to teach a new task after a disruption in the environment.
We anticipate that our AI/ML Software Platform will enable each robot to have a Task Library such that each robot can perform multiple tasks in a variety of situations and switch between them quickly with no reprogramming and minimal, if any, retraining.
Hardware and Management Platform
We envision that our AI/ML Software Platform will be provided to customers along with the following baseline edge computing and training hardware components: a controller component that houses the closed-loop autonomy software framework that interfaces with the robot baseline system; a sensor package for situational awareness; and a human/machine interface system for training and teleoperation . The training and teleoperation interface system is expected to include a motion capture device and hand controller that is available as a standalone package.
Along with our AI/ML Software Platform we are developing a cloud-based customer portal to facilitate software purchases, updates, and online customer support. This customer portal is expected to also include the data analytics, operational tools, and the functionality to monitor, configure, and train the AI/ML Software Platform.
Market Opportunity
We believe the market for AI/ML software for industrial robotics has been experiencing and is expected to continue to experience significant growth, which we believe is driven by a need for more efficient and flexible manufacturing processes.
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Companies such as ABB, Fanuc, Yaskawa, KUKA, and Universal Robots are prominent in providing both robotic hardware and AI-based software solutions to a wide range of industries to promote automation. We believe our AI/ML Software Platform augments their existing capabilities and will be complementary to their products offerings.
Collaborative robots, or cobots, which can work alongside humans, are also an area of opportunity for our AI/ML Software Platform. We expect our AI/ML Software Platform to enhance cobots’ ability to adapt to dynamic or unstructured environments. Further, we believe our AI/ML Software Platform has applicability to the unmanned aerial vehicle (UAV), remotely operated vehicle (ROV) and unmanned ground vehicle (UGV) markets to enable autonomous navigation and functionality especially as it relates to the defense sector. We have a contract with Air Force Research Laboratory (AFRL) that provides funding to explore this potential. Should this be a viable opportunity, we may consider selling our AI/ML Software Platform into the UAV, ROV and UGV markets.
We believe that our initial customer base will be comprised of innovators and early adopters in the industrial manufacturing, warehousing and logistics, defense, infrastructure maintenance and repair, energy and aerospace and aviation industries. We believe that if we are successful demonstrating the value of our AI/ML Software Platform with these early adopters, there will be many potential customers that are fast followers. In the long run, we believe that our AI/ML Software Platform will benefit many markets and industries. However, it is possible that these beliefs and assumptions will prove incorrect, and, as a result, actual results and market sizes may deviate materially from our estimates. See Part I Item 1A Risk Factors - “Our operating and financial projections rely on management assumptions and analyses. If these assumptions or analyses prove to be incorrect, as they often have in the past, our actual operating results may be materially different from our expected or forecasted results. ”
Commercialization & Growth Strategy
Our Anticipated Sales Model
At launch, we anticipate offering our AI/ML Software Platform in at least two different packages: (a) the AI/ML Software Platform with teleoperation devices including a full set of software and hardware needed to facilitate autonomy training and deployment, which is recommended for all first-time customers; and (b) the AI/ML Software Platform without teleoperation devices, which is recommended for customers who have already purchased the AI/ML Software Platform and wish to expand their capabilities across multiple robotic systems.
Continued Development of our AI/ML Software Platform
Our research and development efforts are primarily focused on the further improvement of our AI/ML Software Platform, although some de minimis hardware-related research and development efforts continue. We plan to pursue continuous improvement of our AI/ML Software Platform and to develop additional functionalities, for example certain specific Task Libraries. We believe that as we show the commercial viability and benefits of our AI/ML Software Platform in our initial target markets and use-cases, customers and potential customers will want to use our AI/ML Software Platform to address other use-cases that previously have not been conducive to automation. As our products are highly complex, we want to ensure that we continue to develop new systems and solutions to address new markets and use-cases, and thereby grow our business.
Focused Effort on Commercialization while Collaborating with Development Customers
Our AI/ML Software Platform is in its development phase. We will continue to focus on the development and commercialization of our AI/ML Software Platform to bring the initial commercial version to market in a timely manner targeting specific use-cases. We believe this will prove the benefits of our AI/ML Software Platform in everyday working conditions while confirming market demand and achieving and growing product revenue.
We intend to engage in the future with development customers in various industries. In some cases, these development customers may pay us to develop our products. This approach allows us to reduce our net loss and net use of cash while learning from our future customers’ experience with the AI/ML Software Platform, continuing product development efforts to improve and commercialize our product, and establish relationships with potential commercial and government customers. We believe working with these development customers will allow us to accelerate our brand awareness within our targeted industries and develop products that will meet the needs of a variety of potential customers. We anticipate that these relationships will play an important role in helping us select the markets, use-cases and product capabilities we are currently pursuing.
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Competitive Strengths
30+ Years of Robotics Experience
As a pioneer in the robotic systems industry, we benefit from lessons learned over 30-plus years and significant investment in research and development. Through our development efforts, including our software development efforts, we have developed a significant amount of advanced technology that we are leveraging to develop our AI/ML Software Platform. Our extensive robotics history gives us valuable perspective on how to use software to tackle the challenges associated with training and managing industrial robots in complex and dynamic environments.
We believe that leveraging our previous innovations in hardware and related software, including advances in energetic outdoor mobile manipulation, human like dexterity and immersive teleoperation technology for natural extended reality interactions between humans and robots will enable us to transition our previous software development into a hardware agnostic AI/ML Software Platform to bring the benefits of our software to a much broader base of robots.
We have spent many years working with and listening to people with experience in the industries we expect to target, including advisors and development customers. These early engagements have helped us form relationships with potential customers, helped fund our development efforts and provided critical customer insight and feedback into our development plans and software design. We believe our early efforts to get this feedback and build these relationships with potential customers situate us well to effectively commercialize our AI/ML Software Platform.
Visionary and Experienced Management
We have an experienced and talented team with deep operational expertise. Our team is led by Benjamin Wolff, our Chief Executive Officer, who has many years of executive-level, operational and corporate board experience. Our engineering efforts are led by Denis Garagić, our Chief Technology Officer, with over twenty-five years of experience in AI and ML. Members of our board of directors have extensive experience across a wide array of disciplines.
Competition
We believe we are redefining automation to bring human-like reasoning, intelligence and autonomy to robotics through a unique application of AI and ML that has the potential to significantly accelerate growth for our commercial and defense customers. Our AI/ML Software Platform will compete with companies that have developed or are developing both directly and indirectly competing solutions and capabilities. While there are many automation-centric companies who are active, especially in early-adopter segments such as warehouse and logistics, and select manufacturing or assembly verticals, we believe our primary competitors are those who are focused on addressing key challenges in robotic deployments via autonomy or automation-enhancing software capabilities. In the broader automation landscape, we will compete (both directly and indirectly) with companies such as Bright Machines, C3.ai, Dexterity, Gray Matter Robotics, Intrinsic, Mujin, Olis Robotics, Rapid Robotics, and Ready Robotics. We believe that our competitors are seeking to solve the same or similar industry challenges as we are, but that most are focused on a particular aspect of the functionality of our AI Software Platform rather than a fully competitive solution.
While we view industrial robotics manufacturers, large system integrators, and consulting companies such as Fanuc, Kuka, ABB, Yasakawa, Honeywell, Reply, and Rockwell Automation, as potential target customers and/or channel partners for our software platform, we also recognize that these companies could also emerge as formidable competitors through their own internal development efforts or future technology partnerships with and acquisitions of our direct competitors. They may bring their robust customer relationships, channels and significant financial resources to help accelerate the market viability of one of our direct or indirect competitors.
Many of our competitors and potential competitors have products that are commercially available and/or in development. We expect some products currently in development by such competitors and potential competitors to become commercially available in the next few years.
Our competitor base may change or expand as we continue to develop and commercialize our AI/ML Software Platform and develop new functionality or products, or if we return to efforts to develop and commercialize hardware systems. These or other competitors may develop new technologies or products that provide superior results to customers or are less expensive
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than our products. Our technologies and products could be rendered obsolete by such developments. See Part I Item 1A Risk Factors - “ We operate in a competitive industry that is subject to rapid technological change, and we expect competition to increase. Our products may not be competitive with other alternatives.”
We expect that we will compete favorably due to our technical innovation and product features and performance. Some of our potential competitors have greater financial, technical and other resources than we have. Our competitors may be able to deploy greater resources to the design, development, distribution, promotion, sales, marketing and support of competitive products than we can. Additionally, some of our competitors have greater name recognition, longer operating histories, larger sales forces, broader customer and industry relationships and other tangible and intangible resources than we have. These competitors also compete with us in recruiting and retaining qualified research and development, sales, marketing, and management personnel, as well as in acquiring technologies complementary to, or necessary for, our products. Additional mergers and acquisitions by our existing or potential competitors may result in even more resources being concentrated in our competitors.
Customers and Partners
Through the end of 2023, our customers have primarily been development customers: customers funding our hardware product research and development efforts for which we have suspended development efforts. However, our many years of work with potential customers in many different industries and the U.S. Department of Defense, in particular the Air Force Research Laboratory, has contributed to the development of our AI/ML Software Platform. We do not yet have any customers for our AI/ML Software Platform. We anticipate initial commercial customers for our AI/ML Software Platform will be in industries such as industrial manufacturing, warehousing and logistics, defense, infrastructure maintenance and repair, energy and aerospace and aviation, among others.
Intellectual Property
Our ability to create, obtain and maintain intellectual property is important to our business. We rely upon a combination of protections afforded to owners of patents, copyrights, trade secrets and trademarks, along with employee and third-party non-disclosure agreements and other contractual restrictions to establish and protect our intellectual property rights.
We pursue patent protection at times when we believe we have developed a patentable invention and the benefits of obtaining a patent outweigh the risks of making the invention public through patent filings. We are in the process of attempting to secure patent protection for aspects of our AI/ML Software Platform but none of these patent applications have yet been granted. Due to the fact that our extensive patent portfolio is expensive to maintain, we are in the process of culling patents and applications from our portfolio that we do not believe are essential or likely to add value to our ongoing business operations. Many of our previously issued patents have expired, with others set to expire on dates ranging from 2023 to 2040, exclusive of any patent term adjustment or patent term extension. We do not know whether our pending patent applications will result in issued patents, or whether the examination process will require a narrowing of claimed subject matter. Considering the highly active fields of technology in which we are involved, particularly the field of artificial intelligence, our patents and pending patent applications may not provide us with broad-level protection.
To protect our brand, we also pursue the registration of our domain names and various trademarks in the United States and in select international locations.
Sales and Marketing
Our AI/ML Software Platform is currently under development. While we continue to focus on the further development and commercialization of our AI/ML Software Platform, our sales efforts are underway to engage with potential customers. We intend to leverage many of our relationships built through our previous hardware efforts to sell our AI/ML Software Platform. We anticipate our potential customers to be in a wide variety of industries such as industrial manufacturing, warehousing and logistics, defense, infrastructure maintenance and repair, energy and aerospace and aviation, among others. We intend to invest in our sales and marketing efforts in support of the commercialization of our AI/ML Software Platform.
We intend to pursue strategic relationships with systems integrators, companies with complementary technologies, software application providers, distributors, and consulting firms as and when we deem appropriate to expand the channels in which our AI/ML Software Platform is marketed. We believe working with these partners will accelerate our brand awareness and path
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to market within various industries and provide complementary capabilities and differentiation that will attract new customers while helping us expand our customer base.
We currently expect to offer our AI/ML Software Platform through a term-based licensing model that would result in a recurring revenue stream. We may also offer add-on functionality for an additional license fee. We may charge an upfront fee for the teleoperation devices needed to facilitate autonomy training and deployment or embed the cost into the license fee. We expect to continue discussions with potential customers to ultimately determine the appropriate model. Additionally, while the initial focus of our sales and marketing efforts has been primarily on the U.S. domestic market, we intend to explore opportunities in select non-U.S. markets as and when we deem appropriate.
Suppliers
We have a limited set of suppliers for the minimal hardware components that will be offered with our AI/ML Software Platform. We expect most of our suppliers to be based in the United States and expect most of our supplier relationships to be purchase order based rather than long-term supply contracts. In some cases, we have sole source (where the component is only available from a single vendor, often as a result of customization for our use) or single source (where we purchase from a single vendor but there are alternative sources of the component) suppliers. We seek to minimize our dependence on sole or single source suppliers in order to reduce risk in our supply chain, including the risk of losing a sole or single source supplier due to bankruptcy, discontinuing production of the particular component or some other reason. For additional information related to supply chain issues, see “ Risk Factors— Our AI/ML Software Platform requires certain limited hardware components, and we are dependent on our suppliers, some of which are currently single, sole or limited source suppliers, and any inability of these suppliers to deliver necessary components of our products at the prices, volumes, performance, timing and specifications acceptable to us, could have a material adverse effect on our business, prospects, financial condition and operating results. ”
Government Regulation
We are subject to various U.S. federal, state, and local laws and regulations governing the occupational health and safety of our employees and wage regulations, including the requirements of the U.S. Occupational Safety and Health Act, as amended, and complementary state requirements (including the Utah Occupational Safety and Health Division’s Utah State Plan) that protect and regulate employee health and safety.
We are also subject to U.S. laws and regulations that may limit and restrict the export of our products and services and may restrict our ability to transact with certain potential customers, suppliers, business partners and other persons. These laws and regulations include outright prohibitions on certain types of transactions and impose license or other government authorization requirements on others. We must also comply with export restrictions and other laws affecting trade and investments imposed by other countries to the extent applicable. We maintain export compliance controls and procedures as part of our broader compliance program, but, as with any compliance program, there are risks that these controls might not prevent every instance of non-compliance, in which case we could be exposed to legal liability. To date, compliance with these laws has not significantly hampered our efforts to engage and transact with third parties but could further limit them in the future. Changes in, and responses to, U.S. trade policy could reduce the competitiveness of our products by making it difficult or impossible to enter affected markets, which could have a material adverse effect on our business, prospects, financial condition or results of operations.
Aspects of our use of sensors in connection with our AI/ML Software Platform must comply with the rules of the Federal Communications Commission (FCC), including with respect to: the use of any radio frequency, or RF, spectrum utilized for such components as the remote control or teleoperation system; the power level and frequency of any RF energy emitted (intentionally or otherwise); and any conditions imposed by the FCC on the device certification(s) issued to us or to third parties for any modular transmitters installed in our products. Such rules require, among other things, specific consumer disclosures with respect to RF emissions and proper installation and operation of the device components and any modular transmitters in our products.
Further, as a U.S. government contractor, we are subject to various government procurement and other laws, regulations, and contract requirements, including provisions and clauses of the Federal Acquisition Regulation (FAR), the Defense Federal Acquisition Regulation Supplement (DFARS), and other agency-specific regulations. These U.S. government contracting
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requirements further implicate a broad variety of subjects in addition to the areas described above, including security, data management and disclosure, cybersecurity, cost and pricing activity and finance.
Legal Proceedings
From time to time, we may be subject to legal proceedings. We are not currently a party to or aware of any proceedings that we believe will have, individually or in the aggregate, a material adverse effect on our business, financial condition, or results of operations. Regardless of outcome, litigation can have an adverse impact on us because of defense and settlement costs, diversion of management resources and other factors.
Human Capital
We conducted two reductions in force (each a “RIF” and together the “RIFs”) in the past 12 months, one in July 2023 (the “July RIF”), affecting approximately 24% of our workforce at the time, and another in November 2023 (the “November RIF”), affecting approximately 70% of our workforce at the time, ultimately resulting from our decision to shift our product development and commercialization strategy to focus on our AI/ML Software Platform.
Following the completion of the RIFs, as of February 1, 2024, we had approximately 70 full-time and part-time employees, with most employees located in our Salt Lake City, Utah office. We also engage consultants and contractors to supplement our permanent workforce on an as-needed basis. Approximately 65% of our employees are involved in engineering functions, including research and development. To date, we have not experienced any organized work stoppages and consider our relationship with our employees to be good. None of our employees are subject to a collective bargaining agreement or represented by a labor union.
Facilities
We currently operate in a corporate and manufacturing facility in Salt Lake City, Utah consisting of approximately 61,000 square feet, The lease of our Salt Lake City facility expires in May 2033 and has two options to extend the lease for a three-year period each. As announced on November 14, 2023, we are in the process of winding down our operations in our Pittsburgh, Pennsylvania office. We believe that should we need additional or different space we will be able to obtain such space on commercially reasonable terms.
History, Corporate Information and Website
Sarcos is the result of a decades-long effort in research and development of robotic systems and solutions. Our original predecessor was spun-out of the University of Utah in 1983. In 2007, our predecessor was acquired by Raytheon and was operated until 2014 as a division of Raytheon known as Raytheon Sarcos. During this period, Raytheon Sarcos was focused primarily on developing cutting-edge technologies for use by U.S. governmental agencies. In December 2014, the assets of Raytheon Sarcos were acquired by a consortium led by the former Raytheon Sarcos President and our current Chief Innovation Officer, Dr. Fraser Smith, and technology and telecom entrepreneur Benjamin Wolff, our Chief Executive Officer, President and member of the Board of Directors. This acquisition was the basis for the establishment of Sarcos Corp., a Utah corporation (“Old Sarcos”), which was incorporated in Utah in February 2015 as Sarcos Corp. On September 24, 2021, Old Sarcos merged with Rotor Acquisition Corp. (“Rotor”), a Delaware corporation. On September 24, 2021, Rotor changed its name to Sarcos Technology and Robotics Corporation. In April 2022, we acquired RE2, Inc., (“RE2”) a Pittsburgh, Pennsylvania based robotics company.
On November 14, 2023, we announced a pivot in business strategy to prioritize the development of our commercial AI/ML Software Platform and suspend further commercialization efforts on hardware products, although some de minimis hardware-related research and development efforts continue. After continued analysis of our products and programs and careful consideration of our available cash and other resources, as well as third party dependencies, customer decision timing, and the cost and time to develop and achieve a significant and steady revenue stream from our hardware products, we concluded that focusing on our AI/ML Software Platform and suspending our hardware commercialization efforts gave us the best risk-adjusted opportunity to meet our previously announced goal of pursuing significant near-term revenue tied to acute customer needs and reduce our capital requirements and related risks in line with available resources. We believe that the expected capabilities described above, combined with a large potential addressable market, create an opportunity to build a robust
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software business that has the potential to scale at a substantially faster rate than our hardware solutions. This pivot in strategy builds on our prior announcement, on July 12, 2023, that we had refined our strategy to focus on products that we believed had the most potential for near-term revenue growth and strategic opportunities, which at the time included our Guardian Sea Class system, certain aviation solutions (baggage handling and exterior aircraft maintenance), a solar (solar field panel installation) solution and our commercial AI/ML Software Platform.
Our principal executive offices are located at 650 South 500 West, Suite 150, Salt Lake City, Utah, 84101. Our telephone number is 888-927-7296.
We maintain a company website with the address www.sarcos.com. We are not including the information contained on our website as a part of, or incorporating it by reference into, this Annual Report on Form 10-K. We make available free of charge through the www.sarcos.com website our Annual Reports on Form 10-K, Quarterly Reports on Form 10-Q and Current Reports on Form 8-K, and amendments to these reports filed or furnished pursuant to Section 13(a) or 15(d) of the Exchange Act, as soon as reasonably practicable after we electronically file such material with, or furnish such material to, the SEC. These reports and other information are also available, free of charge, at www.sec.gov. In addition, our Code of Business Conduct and Ethics is available through the www.sarcos.com website and any amendments to or waivers of the Code of Conduct will be disclosed on that website.
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