Thesis
Labor shortages have become a widespread issue across the US, with 4.7 million more job openings than available workers as of August 2024. The manufacturing sector is projected to face a deficit of 3.8 million workers through 2034, while 76% of supply chain and logistics operations report experiencing labor shortages, and retailers anticipate more than 1 million unfulfilled jobs in customer-facing positions in 2025. Labor market growth is expected to be weak, with only a projected increase of 1.8 million (1.1%) people by 2031. This sluggish growth is placing strain across industries.
Meanwhile, another labor-intensive industry is facing shortages as the demand for in-home care is increasing. Globally, over 700 million adults aged 65 and older require some form of assistance, a figure that is expected to rise as populations continue to age. In the US alone, the over-65 demographic is projected to grow to 82 million (47% increase) by 2050. This age group’s share of the total population is also anticipated to rise from 17% to 23% by 2050. The growth in the elderly population is driving a greater demand for in-home care services, further intensifying existing labor shortages.
In 1977, as part of Robot Visions, Isaac Asimov wrote an essay predicting the effect that technological advances and automation would have on human labor:
“I can't help but think, however, that the advance of computerization and automation is going to wipe out the subwork of humanity—the dull pushing and shoving and punching and clicking and filing and all the other simple and repetitive motions, both physical and mental, that can be done perfectly easily—and better—by machines no more complicated than those we can already build. In a properly automated and educated world, then, machines may prove to be the true humanizing influence. It may be that machines will do the work that makes life possible and that human beings will do all the other things that make life pleasant and worthwhile.”
Figure’s long-term vision is to make labor optional by providing every human on the planet with a personal humanoid robot. The company plans to enter commercial labor markets before serving consumer household markets. Through partnerships with OpenAI, Microsoft, NVIDIA, and BMW, Figure aims to develop general-purpose humanoids that make a positive impact on humanity and create a better life for future generations.
Founding Story
Figure was founded by Brett Adcock (CEO) in 2022 in Sunnyvale, California.
Raised in rural Moweaqua, Illinois on a third-generation farm, Adcock credits his family’s work ethic with inspiring an interest in building companies. While pursuing electrical engineering and business administration degrees at the University of Florida in 2004, Adcock built his first venture, Street of Walls, a website aimed at helping undergraduates recruit for jobs in finance. By 2023, the platform had garnered 30 million unique views.
After building Street of Walls and graduating in 2008, Adcock worked as an analyst at two hedge funds covering the staffing and headhunting industries. Through that experience, Adcock identified a major gap: traditional recruiters lacked the advanced technology needed to effectively source top-tier talent. In 2013, Adcock co-founded Vettery with Adam Goldstein, a managing partner at one of the hedge funds Adcock used to work for. Vettery, an AI-powered online marketplace matching human capital to job opportunities, was acquired in 2018 for $100 million by The Adecco Group, a Switzerland-based global HR services firm.
After the successful acquisition, Adcock found himself exploring aviation and hardware due to his passion for solving traffic and building sustainable transportation. In 2018, he co-founded another company with Goldstein called Archer Aviation. He funded the company with his own money and personally built the engineering lab for it at the University of Florida, his alma mater. Aiming to solve the dual problems of urban mobility and sustainable transportation, Archer builds electric vertical takeoff and landing (VTOL) aircraft. They raised a total of $1.5 billion and took the company public through a SPAC deal in 2021 at a valuation of $2.7 billion.
Source: Archer Aviation
After four years, Adcock was ready to move on. He’s still a majority shareholder in Archer, but he “felt like there was a misalignment between [him] and the board.” He also wanted to get focused on “this new AI/robotics revolution.” Stepping away from Archer, Adcock founded Figure in 2022 with $100 million of his own money. Figure’s end goal is to create general-purpose humanoids, or human-size robots, that will replace humans in manual labor roles. To do so, Adcock assembled a team of engineers from a variety of robotics and technology companies like Boston Dynamics, Agility Robotics, Tesla, Rivian, Apple, and Google. He also brought on Dana Berlin (VP of Commercialization & Capital), Lee Randaccio (VP of Growth), and Logan Berkowitz (VP of Business Operations) from Archer and Vettery, and added David McCall (Principal Industrial Designer), Mathew DeDonato (Director of Robotic Systems), Michael Rose (Director of Robot Controls), and Damien Bardon (Director of Humanoid Management System) during the early days of the company.
Given the overlap between robotics research and autonomous vehicles, particularly in areas like battery design and Simultaneous Localization and Mapping (SLAM) development, many members of the Figure team bring experiences from autonomous and electric vehicle design. For example, McCall was previously Senior Automotive Designer at Rivian, Senior Automotive Designer at Audi, Automotive Designer at Faraday Future, and Automotive Designer at Ford. DeDonato was previously Senior Manager of Vehicle Hardware Platforms at both Woven Planet Holdings and the Toyota Research Institute. Rose was previously Lead Robotics Engineer at Arrival, Senior Controls Engineer at Apple, Robotics Engineer at Boston Dynamics, and Roboticist at Google. Past team members include Figure’s founding CTO, Jerry Pratt, who served as a senior research scientist at IHMC for 20 years and received a PhD from MIT in computer science. He left Figure to start his own humanoid robotics company, Persona in June 2024.
Product
Figure’s flagship product line is the Figure series of humanoid robots. As of August 2024, there are two robot models in the product line: Figure 01 and Figure 02.
Figure 01
Designed to closely match the global human average weight (62 kg) and height (5 ft 7.5 in for men & 5 ft 3 in for women), Figure 01 stands at 5 ft 6 in and weighs 60 kg. Core specifications include a 20 kg payload, five-hour runtime, 1.2 m/s speed, and an electric power system. Using a vision language model (VLM) trained by OpenAI, Figure 01’s neural network takes in images at 10 hz through onboard cameras and outputs 24 degrees of freedom actions at 200 Hz. Figure 01 is designed to operate in complex, unstructured real-world environments both autonomously and in response to verbal commands.
Source: Brett Adcock
Figure 01 Progress Updates
Figure 01 was introduced in March 2023 when the company emerged from stealth, releasing a video titled Introducing Figure. The video features a computer-generated image (CGI) rendering of the humanoid robot. In October 2023, the company released additional videos titled Figure 01 Dynamic Walking and Dynamic Walking, both showcasing the bipedal capabilities of Figure 01.
Source: Figure
In January and February of 2024, Figure released two more videos, AI Trained Coffee Demo and Real World Task, showcasing Figure 01’s abilities to complete tasks in both household and corporate settings. The first video demonstrated the robot’s capacity to follow verbal commands to complete a household task (making coffee) after 10 hours of training. The second video highlights its ability in a labor setting, where it autonomously moved boxes at 16.7% of human speed.
Source: Figure
Figure announced partnerships with OpenAI and BMW in 2024.
In OpenAI Speech-to-Speech Reasoning, Figure 01 showcases improved logic and dexterity compared to the earlier coffee-making demonstration. The robot can process verbal commands like “can I have something to eat?”, understand the context (recognize that there is an apple on the table and know it’s food), and perform the action (grabbing the apple to hand to the human who is asking for something to eat). According to Corey Lynch, a Senior AI Engineer at Figure, the integration of OpenAI’s internet-trained AI model gives Figure 01 more advanced reasoning and contextual capabilities.
“We feed images from the robot's cameras and transcribed text from speech captured by onboard microphones to a large multimodal model trained by OpenAI that understands both images and text. The model processes the entire history of the conversation, including past images, to come up with language responses, which are spoken back to the human via text-to-speech. The same model is responsible for deciding which learned, closed-loop behavior to run on the robot to fulfill a given command, loading particular neural network weights onto the GPU and executing a policy.”
Source: Corey Lynch
In BMW Full Use Case, Figure 01’s fully autonomous and AI-driven physical manipulation is showcased at Plant Spartanburg, BMW’s largest automotive exporter in the US with more than 6.3 million BMWs assembled over the past 30 years. In the video, Figure 01 can autonomously place, pick, detect, navigate, and insert car parts into the correct positions while self-correcting any errors in the process.
Source: Figure
Figure 02
Figure 02 was engineered with several advancements over Figure 01, designed to handle up to 20 hours of autonomous work daily. Its exoskeleton structure offers crash protection, while custom-designed appendages and a six-camera vision system enhance physical capabilities. The robot is powered by onboard CPU and GPU processors, with fully integrated wiring and a custom battery pack to ensure seamless operation. Additionally, Figure 02 features enhanced logical reasoning and failure protections. A key upgrade is its fully integrated speech-to-speech conversational ability, with speech set to become the primary interface for all future Figure models.
Source: Figure
After 18 months of development, Figure 02 was unveiled in August 2024. Unlike Figure 01’s computer-generated reveal, the new robot’s reveal featured a live-action demonstration of its capabilities. Notably, it boasts a fourth-generation hand design with 16 degrees of freedom, enhanced AI inference and computation (three times that of Figure 01), and a 2.25 KWh battery, offering 50% more runtime over Figure 01. Apart from physical and technical specifications, Figure 02 has completed a viability trial run at BMW’s Plant Spartanburg, focusing on testing autonomous operations, neural network-assisted manipulation, and self-correcting behavior.
Source: Figure
Use Cases & Design Areas
Figure’s goal is to produce general-purpose humanoid robots designed to perform a wide range of tasks in a world optimized for the human form. First, Figure plans to deploy its robots in corporate labor settings (manufacturing, supply chain, and logistics) before expanding into consumer households. To achieve this goal, Figure is advancing its current and future products in five areas of advancement: system hardware, unit cost, safety, volume manufacturing, and artificial intelligence.
Humanoid Forms
The two primary schools of thought in robotic design are biomimetic and functional. Biomimetic designs seek to translate natural systems (biological forms) into engineering principles. Notable examples include Boston Dynamics’ Spot, the Wyss Institute at Harvard’s RoboBees, and Festo’s BionicKangaroo. On the other hand, functional designs focus on identifying specific hardware requirements and high-level functionalities, analyzing, and integrating unit interactions to address particular scenarios or problems. Prominent examples include iRobot’s Roomba, Kuka’s KR QUANTEC series, and ABB’s YuMi. These design philosophies are not mutually exclusive and robotic design often draws on both approaches to construct viable robots.
Humanoid robots are considered a subset of biomimetic design that focuses on replicating and enhancing the human form. Though researchers differ on whether the humanoid form is most efficient for robotic designs and use cases, Figure believes that multi-functional humanoid robots are best suited for a world where most tasks are already designed for human interactions. Prominent tech figures including Tesla CEO Elon Musk and NVIDIA CEO Jensen Huang have voiced support for this view. In March 2024, Musk, whose company is developing the Optimus humanoid robot, stated that “Earth is already tailor-made for generalized humanoid robots.” Huang agreed with Musk’s sentiment at Computex, a large computer hardware conference in Taiwan, in June 2024, noting that “the easiest robots to adapt into the world are humanoid robots because we built the world for us. We also have the most amount of data to train these robots than other types of robots because we have the same physique.” According to Figure, the development of future Figure robot models will proceed under the following guidelines:
“Our team is designing a fully electromechanical humanoid, including hands. The goal is to develop hardware with the physical capabilities of a non-expert human. We are measuring this in terms of range of motion, payload, torque, cost of transport and speed, and will continue to improve through rapid cycles of development, each cycle as part of a continuum.”
Robotics & Human Safety
Asimov’s Three Laws of Robotics have been a common framework for robotic operating principles since they were introduced in his 1942 short story, Runaround. The moral quandaries Asimov explored have challenged, motivated, and most of all, inspired generations to push the boundaries of the future. Entrepreneurs like Adcock, Musk, and Bezos claim Asimov as an important influence on their philosophies and work. Given the First Law stating that “a robot may not injure a human being or, through inaction, allow a human being to come to harm,” Figure prioritizes human safety as a core tenet of its operating philosophy:
“[Safety is] essential that our humanoids will be able to interact with humans in the workplace safely. We will design them to be able to adhere to industry standards and corporate requirements.”
Adcock has gone on record to say that a “high safety track record will be needed before building trust of the robot in your home.” Dovetailing with the initial business plan to pursue enterprise opportunities and increase capital efficiency early on, Figure has opted to initially enter corporate labor industries where training could be more generalized in a structured warehouse or shipping environment as opposed to the highly unstructured environment of households.
AI-Powered Robotics
While the machine itself is the core physical modality in which a robot takes shape, the difference between the unthinking machine and the learning machine is the implementation of a robust reasoning engine, or artificial intelligence. As early as 1949, the first self-navigating robot relied on three components: sensor technology, a feedback loop, and logical reasoning. The tortoise-like robot could navigate through light sources and recharge itself based on these mechanics. By 1972, the Stanford Research Institute had developed Shakey, a robot that used cameras to create a model of its environment and used a separate planning layer to automatically generate its movements.
While Figure’s technology and in-house vertical integration enable the production of advanced hardware, the company's future success ultimately depends on its distinctive AI and software integrations. “AI/software is now our primary bottleneck in entering the commercial market,” Adcock explains, emphasizing that “Figure is ultimately an AI-first company.” As supply chains mature and hardware becomes commoditized, Figure's success will rely on its ability to integrate VLMs, hardware, and AI to deliver customized robotic solutions. This makes Figure’s final design principle crucial:
“Building an AI system that enables our humanoids to perform everyday tasks autonomously is arguably one of the hardest problems we face long-term. We are tackling this by building intelligent embodied agents that can interact with complex and unstructured real-world environments.”
To achieve this, Figure has established partnerships with major AI leaders and hyperscalers, including OpenAI, Microsoft, and NVIDIA. These collaborations allow Figure to integrate multimodal models using humanoid robot data, engage in high-end deep-learning training for large models on ND H100 Azure GPUs, and enhance simulation with full-stack accelerated systems, libraries, and the GR00T foundation model, a general-purpose foundation model for humanoid robots.
OpenAI’s models are particularly vital to Figure’s speech-to-speech command feature, where OpenAI provides the custom language model that serves as the “brain” for speech reasoning, while Figure handles the lower-level engineering to convert model logic into physical movement. To support these partnerships and AI integration, Figure has diverged from the traditional mechanically-focused approach of past robot developers, hiring over 30 software engineers since inception to incorporate AI into humanoid robotics.
Market
Customer
Figure’s long-term target customers are large enterprises across every industry in need of large-scale labor, except military or defense applications, and retail consumers in need of at-home care. As of May 2022, Figure aimed to have an initial impact on industries where labor shortages are most severe such as manufacturing, warehouse, logistics, and retail.
Source: US Chamber of Commerce
Adcock envisions that by 2030, Figure will expand its reach to retail consumers, targeting 2.3 billion households globally, while also addressing the needs of the 700 million elderly individuals requiring at-home care. In the even longer run, Figure expects use cases to emerge in off-world applications.
Source: Figure
Market Size
The global robotics market was estimated to be $39 billion in 2023 and is expected to grow at a 16% CAGR to a $134 billion market by 2031. Broader estimates for the AI hardware market expect a market size of $128.7 billion by 2033, growing at a CAGR of 23.9% from 2024 to 2033. Figure operates specifically within the humanoid robotics segment, which is expected to reach $38 billion globally by 2035. Between 2024 and 2035, robot shipments are expected to increase fourfold to 1.4 million units, driven by a significant 40% reduction in material costs.
Humanoid robots are typically considered best suited for tasks that are “dangerous, dirty, and dull.” Labor shortages often arise in jobs that pose health hazards, are necessary but unpleasant, or involve repetitive, tedious work. By 2035, the global demand for humanoid robots could reach between 1.1 million and 3.5 million units, assuming a labor substitution rate of up to 15% in industries such as car manufacturing and high-risk sectors like disaster rescue and nuclear reactor maintenance.
Source: Goldman Sachs
Automated systems are expected to account for up to 25% of capital spending over the next five years. Retail and consumer goods will likely emerge as the largest spenders, with 23% of respondents from that sector planning to invest over $500 million. Logistics and fulfillment are projected to allocate the highest shares of their budgets to automation, with these sectors anticipating that automation will comprise 30% or more of their capital expenditures in the coming five years.
Source: McKinsey
Competition
Figure faces competition from numerous humanoid robot startups and established companies, both domestically and globally.
Source: Goldman Sachs
Startups
Agility Robotics: Founded in 2015 and based in Pittsburgh, Pennsylvania, Agility Robotics is developing humanoid robots to address labor shortages in the distribution, retail, manufacturing, and logistics industries. Originally a spin-off from Oregon State University, the company created Cassie, a bipedal robot lacking a torso and perception systems. Cassie set the Guinness world record for the fastest 100-meter run by a bipedal robot in December 2022. Agility’s flagship humanoid robot, Digit, features a unique “backward” leg design that enhances maneuverability in factory and manufacturing settings.
Digit is sold alongside Agility Arc, a cloud automation platform that monitors fleets of Digit robots and integrates with existing client workflows, as well as Arc Accessories, a suite of charging docks, work cells, and control pendants. In October 2023, Agility signed a collaboration agreement with Amazon to test Digit in Amazon warehouses. While both Agility and Figure are focused on humanoid robots for automation and labor replacement, Agility Robotics is more specialized in industrial settings like warehouses and logistics, whereas Figure AI has a broader vision of developing general-purpose humanoid robots for both commercial and household applications. As of September 2024, Agility Robotics had raised a total of $178 million at a valuation of $550 million, with key investors including the Amazon Industrial Innovation Fund, Sony Innovation Fund, Playground Global, and DARPA.
1X: Founded in 2014 and based in Sunnyvale, California, 1X is developing safety-focused AI-powered humanoid robots. 1X’s first commercially available robot, EVE, was designed with a rolling base and a humanoid upper body. As of September 2024, 1X’s core product, NEO, is designed to mimic the human form with bipedal locomotion and biomimetic musculature. NEO can be operated remotely and autonomously. 1X intends to use NEO in the security, logistics, and manufacturing industries to address labor shortages before entering consumer household markets, similar to Figure. As of September 2024, 1X had raised a total of ~$140 million at an estimated valuation between $400 million to $600 million. Key investors include OpenAI, Tiger Global, EQT Ventures, Samsung NEXT Ventures, and ADT Security Services.
Apptronik: Founded in 2016 and based in Austin, Texas, Apptronik is developing general-purpose humanoid robots. Apptronik was originally funded by NASA to develop space-intended humanoid robots Valkyrie 1 and Valkyrie 2. Over time, this work transformed into Apollo, Apptronik’s primary model as of September 2024. Apollo is built modularly and can be mounted on any stationary or mobile base platform. It intends to operate in the warehouse and manufacturing industries before aiming to extend into consumer household markets, similar to Figure. Apptronik signed a collaboration agreement with car manufacturer Mercedes-Benz in March 2024 to test Apollo at its manufacturing facilities. Apptronik bootstrapped until its Series A raise, and, as of September 2024, had raised a total of $28 million at a $109 million valuation. Key investors include Capital Factory, Perot Jain, WorldQuant Ventures, NASA, NSF, and the US DoD.
Incumbents
Tesla: Founded in 2003 and based in Austin, Texas, [Tesla](https://en.wikipedia.org/wiki/Tesla,_Inc.) is a vertically integrated electric vehicle manufacturer and autonomous software developer. Under founder Elon Musk’s direction, the company began developing Optimus, a general-purpose humanoid robot. The robot was revealed at Tesla’s AI Day in August 2021, and prototypes were displayed at Tesla’s second AI Day in September 2022. The latest robot iteration, Optimus Generation 2, was unveiled in December 2023. In May 2024, Tesla showed Optimus performing tasks in a Tesla electric vehicle manufacturing plant. Musk claims that Optimus will be controlled by the same AI system Tesla is developing for the advanced driver-assistance system used in its cars. In June 2024, Musk projected Optimus to enter limited production in 2025 when the company would have over 1K Optimus robots working at Tesla.
Boston Dynamics: Founded in 1992 and based in Boston, Massachusetts, Boston Dynamics is a robotics company developing both highly mobile practical humanoid and non-humanoid robots in the manufacturing, construction, energy, defense, education, and logistics industries. Boston Dynamics’ humanoid robot products include the Atlas line. The first version of Atlas was produced under the direction of DARPA and constructed by Boston Dynamics. The company unveiled a new version of Atlas in April 2024, which is designed to improve on human capabilities, and is intended to address labor shortages in “dirty, dangerous, and demeaning” industries, also known as 3D industries. Boston Dynamics signed a collaboration agreement with car manufacturer and investor Hyundai in April 2024 to test Atlas at manufacturing facilities. Boston Dynamics was originally spun out of MIT and CMU and operated independently until it was acquired by Google in 2013. The company was thereafter acquired by SoftBank in 2017 until Hyundai acquired a controlling stake in the company from SoftBank for $880 million in 2020.
Ubtech: Founded in 2012 and based in Shenzhen, China, Ubtech Robotics is a robotics company developing both humanoid and non-humanoid robots in the commercial and healthcare industries. Ubtech’s humanoid line includes the Walker S, Walker X, Walker, and Panda Robot. The Walker S is Ubtech’s primary humanoid robot model as of September 2024, with integrated VLMs, 3D semantic navigation, integrated LLM reasoning, and object detection to manipulation capabilities. As of June 2024, Ubtech was using Walker S for manufacturing use cases and plans to eventually use the robot model for consumer household use cases, similar to Figure. Ubtech signed a collaboration agreement with car manufacturer Dongfeng Liuzhou Motor in June 2024 to test Walker S at manufacturing facilities. Ubtech‘s IPO raised $130 million in December 2023 and is valued at $4.5 billion USD as of September 2024. Ubtech was formerly backed by key investors Tencent, ICBC, CITIC Securities, Minsheng Bank, and Jinyuang Group.
Business Model
As venture capital dollars flow into deep tech, investors remain wary of high capital expenditure requirements, supply chain immaturity, lower ROI, high-risk profiles, increasing valuations from investor crowding, and long roads to commercialization — let alone profitability. As a humanoid robotics company primarily funded through venture capital, Figure recognizes the necessity of building out protections against the aforementioned risks. Adcock understands the need to balance technical viability with fundraising. Building a viable robot is not enough; reaching venture capital milestones requires a clear path to profitability, scalability, and efficient use of capital.
For the industries targeted by Figure and other humanoid robotics companies, the key measure of ROI is how the robot’s lifetime cost compares to human labor costs and performance. If a robot's total cost exceeds that of human labor, particularly with lower labor quality, it becomes unviable for adoption. The current target price for viable humanoid robots is around $50K, aligning with the annual wage for a single shift of labor at just over $18 per hour. Ultimately, clients don’t care how the technology works; they only care that it delivers the desired solution at the right cost. As Steve Jobs opined, “You‘ve got to start with the customer experience and work back toward the technology - not the other way around.”
Source: Global X ETFs
This manifests in two areas of advancement for Figure: maintaining high-quality standards through simultaneous prototyping and reducing robot unit costs via volume manufacturing. According to the company, Figure’s robot manufacturing and prototyping will have the following two mandates:
“Unit Cost: We’re aiming to reduce individual humanoid unit costs through high-rate volume manufacturing, working towards a sustainable economy of scale. We are measuring our costs through the fully burdened operating cost/hour. At high rates of volume manufacturing, I am optimistic unit cost will come down to affordable levels.
Volume Manufacturing: We foresee not only needing to deliver a high quality product, but also needing to deliver it at an exceptionally high volume. We anticipate a steep learning curve as we exit prototyping and enter volume manufacturing. We are preparing for this by being thoughtful about design for manufacturing, system safety, reliability, quality, and other production planning.”
To implement these mandates, Adcock has repeatedly emphasized the importance of rapid design iterations, prototyping, and testing as Figure’s key differentiators, so much so that it has become a hiring requirement and the company’s primary value. Hardware design is notoriously much slower than software, but Adcock believes that the teams that build, test, and ship faster will lead in the space.
Figure aims to release new hardware and software versions every six months, striving to be first to market. Speed and cost reductions are also the reasoning behind Figure’s vertical integration. While Adcock would rather “buy [parts] than build” to expedite development and market entry, the required technical expertise and supply chain immaturity make vertically integrating hardware stacks essential for complex robotics projects.
Source: Angèle Sahraoui
While Figure has not explicitly outlined its commercialization plans, its business model can be inferred from Adcock’s remarks about making humanoid robotics accessible to both enterprise and consumer clients, along with comparisons to contemporaries like Apple and Tesla. Adcock has emphasized that Figure's strategy prioritizes near-term revenues to facilitate capital raising, with initial use cases targeting the manufacturing, warehouse, logistics, and retail sectors.
At the enterprise level, Figure is likely to adopt established hardware contracts, with multi-year Hardware-as-a-Service (HaaS) or Robotics-as-a-Service (RaaS). This approach will serve as the primary revenue stream from enterprise clients seeking large-scale labor solutions over the viable lifetimes of Figure’s robots.
As a vertically integrated hardware manufacturer and software developer, Figure believes its most fitting consumer comparison is Tesla. The consumer business model may mirror Tesla’s approach, combining one-time hardware sales with monthly or annual subscriptions for accompanying software sold directly to consumers.
Source: Angèle Sahraoui
Traction
As of September 2024, Figure has not disclosed revenue numbers or total robots produced, but the company has developed two iterations of its flagship humanoid robots product line. Figure has also established several partnerships with manufacturing and technology companies including BMW, OpenAI, Microsoft, and NVIDIA to further develop product use cases in manufacturing and AI integration.
As of September 2024, the company has 156 total employees, with over 50% of them in engineering. In August 2024, both Figure 01 and Figure 02 completed a trial run at BMW’s Plant Spartanburg, which operated on a milestone-based approach. The trial identified specific automotive manufacturing tasks the robots could handle, with plans for staged deployments of additional robot models to follow. If Figure can demonstrate the clear value of its robots for BMW and replicate this success with other clients, it may be well-positioned to become a provider of robotic solutions to alleviate human labor shortages.
Valuation
Source: Figure
In February 2024, Figure raised a $675 million Series B round at a valuation of $2.6 billion. The round brought the company’s total funding amount to $854 million as of September 2024. Key investors include Microsoft, OpenAI, NVIDIA, Bezos Expeditions, and Intel Capital.
The Series B round followed a $70 million Series A round from 2023. This round was led by Parkway Venture Capital and joined by participating investments from Adcock, Aliya Capital, Bold Capital Partners, Tamarack Global, FJ Labs, and Till Reuter.
Adcock fully self-funded Figure’s $100 million seed round, highlighting the challenges of securing venture capital for deep tech startups. He noted that many VCs are hesitant to invest in this sector due to the constraints imposed by existing LP mandates, the heavy capital requirements for hardware, longer timelines, and the complexity of deep tech innovation.
In January 2024, Figure announced it had signed a partnership with BMW to “deploy general purpose robots in automotive manufacturing environments.” In June 2022, Adcock shared the company had begun shipping its “first small fleet of humanoid robots.” However, there are no publicly available revenue numbers for the company, and Figure is believed to be pre-revenue as of September 2024.
Key Opportunities
Robots for Households & Aging Populations
Automation of everyday household tasks and care for aging populations serves as a tailwind for humanoid robotics development. Current estimates suggest that retail consumers represent 2.3 billion households globally, while over 700 million people make up the aging population in need of at-home care.
Source: Goldman Sachs
However, households pose a greater technical challenge than most industrial labor environments. Homes are unstructured environments with high human density, requiring robots to maintain reliability and safety standards while performing far more advanced tasks. This challenge is reflected in Moravec’s paradox, where relatively simple tasks for humans (laundry, cooking, cleaning) become monumental training hurdles for any household robot.
As a result, Figure plans to enter the consumer household market in the medium term, following successful commercialization in corporate labor sectors. In October 2023, Adcock projected humanoid robots would likely enter households by 2030, after “millions of robots” have been deployed in commercial labor markets. Previews of how Figure robots might integrate into homes can be seen in various showcase videos, including OpenAI Speech-to-Speech Reasoning, Real World Task, and AI Trained Coffee Demo.
Vertical Integration
Peter Thiel has argued that vertically integrated, complex monopolies are an “under-explored modality of technological progress.” Historically, companies that were able to accomplish monopolistic vertical integration were capital-intensive hardware companies. Prominent examples include Standard Oil, Ford, Intel, Tesla, and SpaceX. Thiel continues:
“It's typically fairly capital intensive… we live in a culture where it's very hard to get people to buy into anything that's super complicated and takes very long to build. I think the key to [Tesla and SpaceX] was the complex vertically integrated monopoly structure they had. If you look at Tesla or SpaceX… there was no sort of single massive breakthrough. But what was really impressive was integrating all these pieces together and doing it in a way that was more vertically integrated than most other competitors.”
Figure emulates the vertical integration model in hopes of creating a sustainable competitive advantage in the robotics industry. Though Figure began with a buy-over-build model to prioritize go-to-market speed, the lack of existing manufacturing expertise and supply chain immaturity forced Figure to vertically integrate every step of the robot production process. According to Adcock, Figure “is vertically integrated and design[s] everything in house: motors, sensors, actuators, structures, battery systems, embedded SW, firmware, controls, AI systems, etc.”
For Figure, vertical integration solves for both cost and speed. By taking control of its design, supply chain, and manufacturing processes, Figure can “reduce individual humanoid unit costs through high-rate volume manufacturing” and prevent go-to-market delays caused by third-party suppliers or manufacturers. As of August 2024, with full vertical integration in place, Adock plans to drive low-cost, high-volume production by 2025. In an industry where cost efficiency and rapid innovations are critical, vertical integration enables Figure to scale effectively.
Figure’s vertical integration is further supported by trends in manufacturing on-shoring and favorable federal policies, particularly in technology-focused sectors like electric and factory manufacturing. Legislation such as the Infrastructure Investment and Jobs Act ($1.2 trillion in direct spending and incentives), the Inflation Reduction Act ($370 billion in tax incentives), and the CHIPS Act ($50 billion in direct spending) have made domestic manufacturing increasingly attractive amid rising geopolitical risks. By establishing local manufacturing in the US, Figure can take advantage of government incentives, subsidies, and partnerships aimed at bolstering domestic industrial capacity, enhancing its vertical integration efforts.
Key Risks
Graveyard of Attempts
As of February 2024, no company has achieved the holy grail, which is to create humanoid robots with integrated AI capabilities for a $50K price tag. Figure candidly acknowledges that the path to viable humanoids will be difficult and cautions that the “journey will take decades” along with “billions of dollars invested,” all while facing “high risk and extremely low chances of success.” However, data points like the increasing disparity between labor costs rising and the cost of robotics falling, companies in this space are optimistic.
Source: McKinsey
Hardware Capabilities
Historically, one of the main obstacles to creating commercially viable humanoid robots has been the lack of sufficiently advanced hardware that can match or exceed human capabilities. Compounding this challenge is the high cost of developing such advanced hardware. For instance, in September 2010, a leading humanoid robot, ASIT’s HRP-4, was priced at $300K. By February 2024, the price range for humanoid robots varied significantly, with lower-end models estimated at around $30K and state-of-the-art versions reaching up to $150K per unit.
Source: Goldman Sachs
Despite significant reductions in costs, finding the right balance of power efficiency, mobility, dexterity, and durability in humanoid robots continues to be a persistent challenge, especially due to the immature supply chain for robotic components. Bottlenecks in sourcing and integrating high-quality parts, such as actuators and sensors, into a cohesive system that can reliably perform human tasks across various environments hinder testing speed and machine capabilities. If Figure does not effectively tackle these hardware challenges, it risks producing robots that are either too expensive or unsuitable for practical consumer applications.
Source: Goldman Sachs
Scaling Volume Manufacturing & Cutting Unit Costs
While Figure seeks to reduce unit costs through volume manufacturing, the shift from prototyping to mass production presents significant challenges. Currently, Figure operates with vertical integration due to the absence of third-party manufacturing capabilities and mature supply chains. Scaling up to mass production will necessitate substantial capital investment in building factories and establishing supply chains, further complicated by the lack of existing infrastructure for humanoid robots.
Unlike Tesla, which could leverage existing automotive manufacturing facilities to transition to electric vehicle production, Figure faces the challenge of developing entirely new manufacturing processes and facilities specifically designed for humanoid robots. This entails not only constructing factories but also creating specialized equipment, training a skilled workforce (until the robots are capable of building themselves), and establishing a reliable supply chain for high-precision components that meet the rigorous demands of humanoid robotics. Avoiding volume manufacturing is not an option. Adcock has consistently emphasized that “the only way out is through.” Lowering unit costs and scaling production for commercialization will require Figure to carefully manage its current capital while seeking additional funding to ensure it can grow without compromising go-to-market speed, product quality, or financial stability.
AI & Software Capabilities
The reasoning engine that drives humanoid robots is as crucial as the hardware itself. Without AI models that train robots to execute a range of specialized tasks tailored to specific labor market needs, humanoid robots cannot deliver the quality of work necessary at a reasonable cost to effectively replace humans or non-humanoid robotic models. There are two significant risks involved: first, AI research may struggle to keep up with the demands of humanoid robotics due to a shortage of high-quality training data and second, the integration of AI software with robotic hardware presents substantial challenges.
Though AI models have developed at breakneck speed since the “ChatGPT” moment in 2022, AI progress has since slowed due to a lack of data availability. As companies like OpenAI, Anthropic, Google, and Meta compete to create better models, the amount of data needed increases. Estimates project as many as 60 trillion to 100 trillion tokens of data needed for GPT-5 (GPT-4 was estimated at 12 trillion). According to Paul Villalobos, an AI researcher at Epoch AI, “harnessing all the high-quality language and image data available could still leave a shortfall of 10 trillion to 20 trillion tokens or more.” Even synthetically generated AI data may not serve as a long-term solution, with worries that “increasing synthetic data intake” will “pollute LLM AI models.”
Source: AI: Reset to Zero
Figure believes that AI software integration will be the key differentiator among humanoid robotics companies. Recognized as one of the most challenging technical tasks in robotics, successful integration requires seamless communication between software and hardware. This ensures that robots can autonomously interpret sensory data, make decisions, and execute physical actions in real time. Achieving this requires not only highly optimized algorithms that function within the robot's processing power, energy limitations, and physical manipulation capabilities, but also the flexibility to adapt to changing environments.
Integrated AI models must precisely control the robot's movements, coordinating multiple actuators and sensors to replicate human actions accurately. Any discrepancies between software commands and hardware execution can result in compromised labor quality and raise safety concerns. Furthermore, the necessity for ongoing updates, with Figure aiming to implement updates every six months, adds another layer of complexity, as changes in software often require corresponding adjustments in hardware, and vice versa. This creates a resource-intensive cycle of continuous iteration. Without effective integration, Figure will struggle to unlock the full potential of humanoid robots, hindering adoption and limiting their positive impact on industries and society.
Crowded Market
The market for humanoid robots is growing increasingly competitive. From incumbents like Boston Dynamics and the Toyota Research Institute to newcomers like Tesla and Agility Robotics, more than 16 established companies are racing to market. Despite this, Adcock and former Figure CTO Pratt remain unconcerned about competition. Pratt remarked, “I think it’s just a question of getting there... there’s room for several companies, and I think we can be one of them.”
Source: Joe Musselman
Differentiation among robotic models will hinge on the speed of iteration and time to market. However, as hardware becomes commoditized, the strength of software integrations with that hardware will take on greater significance. To sustain its development and market share after commercialization, Figure must carefully manage its speed to market while continually innovating its humanoid robot products to effectively capture market share from competitors.
Source: Global X ETFs
Brett Adcock’s Track Record
Brett Adcock has had professional success in the past, such as building Street of Walls to 30 million unique views and selling Vettery to The Adecco Group for $100 million. However, one potentially concerning sign for the future of Figure is Adcock’s experience building Archer Aviation. While the company went public via SPAC in September 2021 at a peak market cap of ~$2.3 billion, it has come down to ~$1.2 billion as of September 2024. In addition, despite claiming to have an indicative order book of $6 billion in August 2024, the company has yet to generate any revenue as of September 2024.
Some research reports have pointed to Archer Aviation’s limited flight activity, recycled video marketing materials, misleading DoD contracts, and partner agreements that were “bought with cheap warrants” as indicators that despite the company’s significant promises, there was limited substance to back them up. In particular, Adcock’s separation agreement from Archer Aviation in April 2022 included accelerated vesting for his shares in, what one August 2023 report called, a “stealthy divorce… [including] accelerated vesting of a huge chunk of insider stock to permit selling sooner (which has commenced), while the circumstances of that breakup have never been fully disclosed for investors to evaluate its materiality.”
In addition, there are questions about the quality of the team that Adcock has assembled at Figure. Despite reportedly being pre-revenue, the company has already filled executive positions like VP of Growth and VP of Commercialization and Capital, many of which are filled by executives who have been with Adcock through Archer, and even Vettery. And while Figure does have director-level positions over more technical operational areas such as humanoid management systems, many of these technical executives previously held roles at Archer over significantly different areas, like vehicle management systems.
In particular, the company’s technical bench in AI seems somewhat limited. The majority of AI engineers joined the company less than a year ago as of September 2024, and none of them are particularly senior. In a September 2024 interview with Contrary Research, one AI and robotics investor indicated that conversations they had previously had with either former employees or AI researchers familiar with the team led them to believe “the intelligence in the [Figure] robot is near zero.”
If Archer Aviation is a cautionary tale for the potential future of Figure, it causes concerns for the company’s ability to actually commercialize its products and achieve meaningful success. Instead, the downside case could be that Figure is able to attract meaningful hype and attention, but could fail to deliver any meaningful results.
Summary
Figure was founded by Brett Adcock in 2022 with the express goal of liberating humans from manual labor and enhancing global productivity. The company produces one core product: the Figure humanoid robot series. As of 2024, the Figure line includes two model iterations, Figure 01 and Figure 02, which feature speech-to-speech user interfaces, onboard VLMs, and advanced manipulation hardware to perform AI-powered autonomous work.
By 2025, Figure aims to achieve low-cost, high-volume manufacturing of its robot models, focusing on commercial labor opportunities and expanding into consumer household markets by 2030. The company’s success depends on its ability to maintain rapid technology iteration, software-hardware integration, and cost-effective manufacturing scaling. If done successfully, Figure could become a leading force in making humanoid robots as ubiquitous as smartphones, ushering humanity into a new age of automated work.