D

Dexmate

AI-powered dexterous manipulation robotics platform

Overview

Dexmate develops AI-powered robots with dexterous manipulation for industrial and research use. Its flagship Vega is a dual-armed, mobile humanoid with an omnidirectional base and a foldable torso, reaching up to 7'2" for transport and operations. Vega runs on Nvidia AGX Orin for edge computing, has high-payload arms totaling 15 kg, and uses dexterous hands controllable via a Python API; it combines AI-driven manipulation with remote human teleoperation through its Robot Copilot system and aims for a future Robot Autopilot. The company differentiates itself with embodied AI and precise dexterity on a mobile platform, serving warehousing, logistics, manufacturing, and healthcare pilots, and pursuing easy integration with existing workflows. Dexmate’s goal is to reduce labor shortages and boost efficiency by evolving from copilot to fully autonomous autopilot in real-world settings, supported by partnerships like LG CNS.

Significant Headcount Growth

Work here?Claim your company

About Dexmate

Simplify's Rating
Why Dexmate is rated
C+
Rated C on Competitive Edge
Rated B on Growth Potential
Rated C on Differentiation

Industries

Robotics & AutomationIndustrial & ManufacturingAI & Machine Learning

Company Size

51-200

Company Stage

N/A

Total Funding

N/A

Headquarters

Santa Clara, CA

Founded

2024

Get referred to Dexmate

See people who can refer or advise you

Simplify Jobs

Simplify's take

What believers are saying

  • NVIDIA highlighted Dexmate on November 9, 2026 for Isaac Sim manipulation work.
  • Dexmate signed a 36,000-square-foot Fremont lease on August 27, 2026.
  • RobotToday listed Vega with 10-plus hour runtime and 2026 commercial availability.

What critics are saying

  • Dexmate has 11-50 employees while Figure, Apptronik, and 1X outspend it.
  • Vega faces better-funded rivals from Unitree, Figure, Apptronik, and 1X in 2026.
  • If pilots stay warehouse demos, Dexmate's teleoperation-first model never reaches autonomy.

What makes Dexmate unique

  • Vega is commercially available, wheeled, dual-armed, and compactable for transport.
  • Dexmate pairs hardware with a Physical AI platform and remote teleoperation.
  • NEC invested August 25, 2026; LG CNS backs Dexmate's full-stack robotics thesis.

Help us improve and share your feedback! Did you find this helpful?

Growth & Insights and Company News

6 month growth

15%

1 year growth

1%

2 year growth

20%
4RFV
Nov 9th, 2026
Practice makes precise: at CoRL, NVIDIA and partners reveal how robots rehearse delicate work in Simulation.

Practice makes precise: at CoRL, NVIDIA and partners reveal how robots rehearse delicate work in Simulation. 09/11/2026 Simulation, which has long been the proving ground for robots learning to walk, roll and hop, is now helping researchers teach robots tasks that require a finer touch: aligning gears, connecting cables and assembling small components. The shift from locomotion to manipulation is taking center stage at this week's Conference on Robot Learning (CoRL) in Austin, Texas, alongside the rise of agentic robotics - a new paradigm that integrates frontier agents to create interpretable code for physical robotics systems. At CoRL, NVIDIA is introducing new open robotics technologies, including world action models, simulation tools, benchmarks and agentic workflows. Two NVIDIA papers are among six finalists out of thousands of submissions for the Best Paper Awards at CoRL: GRAIL (Generating Humanoid Loco-Manipulation from World Models), which presents a digital generation pipeline for 3D assets and simulator-ready scenes for robot learning. RoboTTT: Context Scaling for Robot Policies, which introduces a robot model and training recipe that scales visuomotor context three orders of magnitude beyond state-of-the-art policies without growing inference latency. These advancements help researchers train robots on complex tasks, evaluate their performance across changing conditions and use failures to guide further learning - building the precision, adaptability and autonomy needed to move from lab demonstrations to industrial deployment. NVIDIA is working with partners like Ambi Robotics, Bosch Research, Dexmate, Dyna Robotics, FieldAI, Flexion, Noitom Robotics, Siemens, Skild AI, RLWRLD, UC Berkeley, Walden Robotics and the University of Washington to bring these advancements to the broader robotics community. World Action Models Enable Next Level of Robot Autonomy The next level of robot autonomy requires robots to perceive their surroundings, anticipate how their actions will change the environment and execute complex, multistep tasks with a high degree of precision. World action models enable exactly that. At CoRL, NVIDIA is introducing GR00T 2, an open frontier world action model built on NVIDIA Cosmos. Trained on diverse robot and human data, including 100,000 hours of NVIDIA open source human egocentric data, the model enables robots to learn dexterous manipulation skills. Key features include: Out-of-the-box performance: Completed 40 of 50 evaluated tasks at least once without task-specific demonstrations. Skill transfer: Learns from human demonstrations and transfers skills between different robot bodies without robot demonstrations Generalization with little data: Achieved 71% average success across 50 tasks with just one demonstration per task, increasing to 95% with five. Agent control: AI agents can use GR00T 2's application programming interface and supporting tools to run skills in sequence and recover from errors. GR00T 2 currently ranks among the top three models across all vision language action and world action model categories for the RoboCasa365, RoboLab, RoboDojo and MolmoSpaces benchmarks, with multiple leaderboard wins. Nexuni is testing it for robotic laundry handling, Foxconn is applying GR00T 2 to factory automation for server manufacturing and Siemens is evaluating it across industrial use cases. MicroAGI is using GR00T 2, post-trained through reinforcement learning, to perform Ethernet cable swapping with a YAM robotic arm. Its agentic robotics approach automates the creation and calibration of simulation environments using Isaac Lab 3.0 and Newton, where the policy is trained. Training capable robots requires diverse data. Open NVIDIA workflows and models equip researchers with better tools for data collection and annotation: For researchers building robot-training datasets, NVIDIA's new open Video to Data workflow turns human video into simulated robot demonstrations, with a challenge inviting researchers to advance it. The NVIDIA EgoHand open model - being demoed at CoRL and with over 40,000 Hugging Face downloads in the two weeks since launch - reconstructs 3D hand motion, trained with data from Noitom Robotics. Where the Training and Scaling Happens - in Simulation A pretrained model gives robots a core set of skills. Simulation lets researchers train, refine and evaluate skills at scale before deploying them on physical robots. NVIDIA Isaac Lab, an open source robot-learning framework, provides the foundation for that work. Its latest release, Isaac Lab 3.0, allows researchers to use agents to quickly set up training environments with simulation-ready assets, switch between NVIDIA PhysX and Newton physics solvers, choose renderers for perception-based training and apply a new reinforcement post-training library to foundation models like GR00T. Accurate physics is critical to transferring learned skills from simulation to the real robot. Tighter integration with Newton, an open source physics engine, now allows Isaac Lab to model deformable objects such as cables and cloth, along with complex articulated systems such as robotic hands with many interacting joints. Integration with Newton simulates how a strawberry deforms under a robot's grip. Together, Isaac Lab and Newton combine accurate physics with scale to enable researchers to train thousands of simulated robots in parallel. In a vision-based dexterous manipulation benchmark, Isaac Lab 3.0 with Newton achieved up to 2.5x the training throughput of Isaac Lab 2.3 with PhysX. Isaac Lab supports robot simulation with Newton and NVIDIA PhysX. Developers are extending Newton'

GlobalRika
Oct 23rd, 2026
Buy, build or partner: how Korea's big groups are assembling the robot industry.

Buy, build or partner: how Korea's big groups are assembling the robot industry. Updated: Oct 24 Korea has the highest density of industrial robots in the world, and its largest companies now want to own the next generation: humanoids, service robots and the software that runs them. But they are not all doing it the same way. GlobalRika mapped the major deals since 2018. Three playbooks stand out: buy outright, buy step by step, and build a portfolio. And in between the robot makers, a new layer of Korean software companies is emerging. 1. Hyundai: buy the leader. Hyundai Motor Group took the boldest route. In June 2021, it acquired 80% of Boston Dynamics at a valuation of about US$1.1 billion, with SoftBank keeping 20%. In July 2026, after SoftBank exercised its put option, Hyundai agreed to buy SoftBank's remaining stake. The logic is simple: Hyundai bought the most famous robot company in the world and made its own car plants the first customer. Boston Dynamics' Atlas humanoids are scheduled to start work in Hyundai's Georgia plant in 2028. 2. Samsung: step by step. Samsung Electronics moved more cautiously. In early 2023, it bought just under 15% of Rainbow Robotics, a humanoid spin-off from KAIST, for about KRW 87 billion (about US$65 million), and secured a call option on more shares. On December 31, 2024, it exercised part of that option for about KRW 267 billion (about US$200 million), raising its stake to 35% and becoming the largest shareholder. At the same time, Samsung set up a Future Robotics Office reporting to the CEO, led by Rainbow's founder, KAIST professor Oh Jun-ho. In 2026 it added a robotics business unit, and Rainbow's RB-Y1 humanoid has been supplied to Coupang logistics centers. Samsung also invests outside Korea, including in the US robot foundation model company Skild AI. 3. LG: build a portfolio. LG has spread its bets. It took about 10% of Robotis, a maker of robot actuators and educational robots, in 2018, and was an early investor in Angel Robotics, a wearable robot company. In 2024 it invested US$60 million in Bear Robotics, a Silicon Valley serving-robot company, and took control in 2025. Its venture arm, LG Technology Ventures, has backed US humanoid and robot AI companies such as Figure AI and Skild AI, and LG CNS invested in US robot maker Dexmate in 2026. Meanwhile, LG is building its own actuators and humanoids at home, as GlobalRika covered in its LG post. 4. Clobot: the software in the middle. Not every important Korean robot company makes robots. Clobot, a 2017 spin-off from the Korea Institute of Science and Technology (KIST), makes software that lets robots from different makers move and work together. Its CHAMELEON platform handles autonomous navigation, and CROMS manages mixed fleets of robots. That neutral position has made Clobot a partner to almost every camp. Hyundai Motor Group put seed money into Clobot in 2018 through its open innovation arm ZER01NE, and the ties have deepened since. At the end of 2024, Clobot signed a contract to supply a Hyundai manufacturing plant with a patrol solution built on Spot, the four-legged robot from Hyundai-owned Boston Dynamics, running Clobot's navigation and control software. In other words, Hyundai bought the robot maker, and a Korean software company makes the robot useful on Hyundai's own factory floor. Clobot works with more than 20 robot makers, including Boston Dynamics and Unitree, and signed a business agreement with Samsung-backed Rainbow Robotics in 2025. Its CHAMELEON software has been supplied to more than 100 companies, including Hyundai and SK hynix, and it built a multi-robot control system at Incheon Airport with LG CNS. Lotte's accelerator was another early investor. Clobot listed on KOSDAQ in October 2024 at KRW 13,000 (about US$10) a share, with retail demand more than 1,000 times the shares offered. Hyundai is also building robot integration inside the group. In October 2026, its IT affiliate Hyundai AutoEver unveiled a security patrol service using MobED, a mobile robot platform from Hyundai and Kia's Robotics Lab, and now calls itself a robot system integrator. For Clobot, the Hyundai group is both an early backer and a customer, and increasingly a capable in-house player. In 2026 Clobot shifted from software to scale. It agreed in June to acquire Doosan Logistics Solution, Doosan's warehouse automation business, for KRW 68.5 billion (about US$52 million), and raised new capital through a large rights issue to fund the deal and overseas expansion, including a North American subsidiary. Its hardware sourcing subsidiary, ROAS, had already won a US$6 million logistics automation project in North America. Some early strategic investors have started to sell down, a normal step after a listing. 5. The rest of the field. Doosan Robotics, a collaborative robot maker, listed in 2023 and bought US integrator ONExia in 2025 after two attempts to merge with Doosan Bobcat were withdrawn. HD Hyundai Robotics raised KRW 180 billion (about US$135 million) before a planned IPO, at a valuation of about KRW 1.8 trillion (about US$1.35 billion). Hanwha spun off Hanwha Robotics in 2023. The government is also pushing. In April 2025, the trade ministry launched the K-Humanoid Alliance with about 40 companies, universities and research institutes, aiming to build a shared robot AI model by 2028. What this means for startups, investors and EDOs. Korean strategic money is real, and structured. Minority stakes with call options, as in Samsung-Rainbow and LG-Bear, are a common route to control. Founders should expect deal terms that leave room for a later takeover. US companies are part of the plan. Bear Robotics, ONExia, Figure AI, Skild AI and Dexmate all show Korean groups buying or backing US robotics firms. These subsidiaries often become the base for further US expansion, which matters for economic development organizations. Software and integration are the gaps. Korea has hardware makers and big buyers. Fleet software, integration, safety and training data are where outside partners, and companies like Clobot, find room. Watch the listings. HD Hyundai Robotics, Bear Robotics and others are heading toward the public markets. Listings change investor priorities and often bring new partnership and M&A activity. The bottom line. Korea's robot industry is being assembled by a handful of groups, each with its own playbook. Hyundai bought the leader, Samsung climbed step by step, and LG built a portfolio. For outside companies, the question is not whether Korean capital is interested in robotics, but which door, and which deal structure, fits best. If you are a robotics company, an investor or an economic development organization looking to work with Korean groups, GlobalRika would be glad to help. Contact GlobalRika at [email protected]. About the data Deal figures are from company announcements, regulatory filings and Korean media reports through October 2026. Stake percentages can change with later share issues and should be checked against the latest filings. Some transactions, such as the Boston Dynamics stake purchase and the Doosan Logistics Solution acquisition, were pending at the time of the cited reports. US dollar figures are approximate, converted at about KRW 1,330 per dollar. * Hyundai Motor Group newsroom and Bloomberg, Boston Dynamics deals (2021, July 2026) * Etoday, Smart Today and News Tomato, Samsung-Rainbow Robotics stake (2023-2025) * LG newsroom and Newsis, Bear Robotics investment and control (2024-2025) * Hankyung, LG's robot portfolio and Bear Robotics stake (September 2026) * Robot Newspaper (irobotnews), Clobot company profile (November 2025) and Doosan Logistics Solution agreement (June 2026) * Financial News, Hyundai AutoEver robot patrol solution (October 22, 2026) * Money Today, Clobot rights issue and investor sales (April 2026) * The Bell, HD Hyundai Robotics pre-IPO round (2025-2026) * ZDNet Korea, K-Humanoid Alliance launch (April 2025)

Robotics & Automation News
Aug 25th, 2026
NEC invests in US-based robotics startup Dexmate.

NEC invests in US-based robotics startup Dexmate. Japanese technology giant NEC's corporate venture capital fund has invested in US-based robotics startup Dexmate, developer of the VEGA humanoid robot and an integrated physical AI development platform. The investment was made through the NEC Orchestrating Future Fund (NOFF), with NEC and Dexmate planning to explore opportunities to deploy physical AI technologies across a range of industries. Founded in 2024 by AI robotics researchers, Dexmate is developing VEGA alongside a software platform designed to simplify the development, configuration and operation of AI-powered robots. The company says its integrated approach addresses some of the challenges involved in deploying physical AI systems, which can require the coordination of sensors, control systems, training data, simulation environments and site-specific tuning. By bringing these elements together, Dexmate aims to streamline the process from developing robots for particular applications through to deploying them in real-world environments. Discover more Automation System Design Industrial Robot Parts Tao Chen, co-founder and CEO of Dexmate, says: "Robotics & Automation News is honored to welcome the investment from the NEC Orchestrating Future Fund and deeply appreciate their confidence in its Physical AI technology. "Dexmate's humanoid robot "VEGA" and integrated Physical AI development platform fundamentally lower the barriers to robot development and deployment by enabling anyone to easily design, configure, and operate AI-powered robots in real-world environments. "Through this strategic partnership with NEC and their global expertise, we look forward to deploying our technology at scale and jointly accelerating the real-world implementation of Physical AI across a wide range of industries." The investment comes as technology companies increasingly look beyond generative AI operating primarily in digital environments toward physical AI systems capable of interacting with objects, people and real-world surroundings. Robotics is emerging as one of the main areas for the application of these technologies, particularly as developers combine increasingly capable AI models with advances in perception, simulation and robotic control. NEC says it intends to combine Dexmate's technology with its own AI capabilities and experience across multiple industries to investigate potential applications. Shigeki Wada, corporate senior vice president at NEC, says: "NEC has long been engaged in the research, development, and real-world implementation of AI technologies. "Through dialogue with Dexmate, we aim to explore new possibilities for value creation in the Physical AI domain and, together with our partners, contribute to solving the challenges faced by customers and society." The NEC Orchestrating Future Fund operates as an ecosystem-based corporate venture capital fund supporting startups that could complement NEC's technologies and business activities. NEC says the investment in Dexmate forms part of its broader open innovation strategy, through which the company works with startups and other partners to develop new businesses and technologies. Neither company disclosed the value of the investment.

MarketScreener
Aug 25th, 2026
NEC's Orchestrating Future Fund invests in Dexmate's humanoid robot VEGA and Physical AI platform

NEC Corporation's venture capital fund, NEC Orchestrating Future Fund, has invested in Dexmate, a US startup founded in 2024 that provides the AI-controlled humanoid robot "VEGA" and a Physical AI development platform. Dexmate was established by AI robotics researchers and offers an integrated solution combining its humanoid robot with a platform that enables easy development, configuration, and operation of AI-powered robots. The technology aims to streamline robot development and deployment whilst lowering barriers to entry. The partnership will explore collaboration opportunities for implementing Physical AI across various industries. NEC plans to combine Dexmate's technology with its own advanced capabilities and industry expertise to accelerate real-world applications of Physical AI.

Next Move Strategy Consulting
May 29th, 2026
What is driving the next wave of Articulated Robot adoption in 2026?

What is driving the next wave of Articulated Robot adoption in 2026? Published: May 29, 2026 The growth of the Articulated Robot Market is being driven by a fundamental shift across manufacturing, logistics, and research environments. Organizations are increasingly moving beyond traditional automation systems and adopting more flexible robotic solutions capable of handling complex, variable, and precision-driven tasks. This transition reflects a broader industry focus on improving operational efficiency while addressing the growing need for adaptability in modern production and research settings. Recent developments from LG CNS, along with the collaboration between Techman Robot and Tesollo, highlight how articulated robots are evolving from standalone automation tools into strategic assets that support robot transformation (RX) initiatives. As industries continue to prioritize greater flexibility, productivity, and accuracy, the Articulated Robot Market is witnessing increased demand for advanced robotic systems that can support next-generation automation strategies across diverse industrial applications. How are articulated robots expanding beyond traditional manufacturing? Historically, articulated robots were primarily associated with repetitive industrial production tasks. However, recent deployments indicate a much broader application landscape. LG CNS has integrated articulated robotic systems across manufacturing facilities, logistics centers, research laboratories, battery material processing operations, and product development environments. This expansion reflects a growing demand for automation solutions that can operate effectively in settings where precision and flexibility are equally important. One notable example involves a robotic system combining a Doosan Robotics articulated robot with an OnRobot gripper at an LG Unicharm research laboratory. The deployment automated powder measurement processes that were previously performed manually. The system reportedly improved measurement precision from approximately 0.5 grams to an error margin of around 0.05 grams. According to LG CNS, such laboratory automation can shorten product development timelines by as much as 50%. How is physical AI increasing the strategic importance of articulated robots? One of the most significant themes highlighted by LG CNS is the rise of physical AI. Physical AI refers to artificial intelligence technologies that enable robots to perceive, understand, and respond to real-world environments. As industrial operations become increasingly dynamic, conventional programmed automation often struggles to adapt to changing conditions. By incorporating physical AI capabilities, articulated robots can react more effectively to environmental variations, perform complex tasks with greater autonomy, and operate in less predictable settings. This evolution moves robotics beyond repetitive execution and toward intelligent decision-making. To strengthen its position in this area, LG CNS has invested in robotics AI specialist Skilled AI and humanoid robot developer Dexmate while expanding research activities in South Korea and Silicon Valley. How are power electronics enhancing Articulated Robot performance? This illustration highlights the ecosystem of power supply and power conversion components that support articulated robot operations in industrial environments. At the center is an articulated robotic arm used for manufacturing and automation tasks, while the surrounding components represent various AC-DC and DC-DC power solutions required to ensure stable, efficient, and reliable robot performance. The image demonstrates that articulated robots depend not only on advanced mechanical design and control software but also on sophisticated power management systems. Components such as AC-DC power supplies, DC-DC converters, and integrated power modules enable robots to maintain precise motion control, handle varying workloads, and operate continuously in demanding industrial settings. The visualization emphasizes the interconnected relationship between robotics hardware and supporting power electronics infrastructure. How are adaptive grippers making articulated robots more flexible? One of the biggest challenges in industrial automation has been handling diverse product types without extensive reconfiguration. Techman Robot and Tesollo addressed this challenge through an integrated solution that combines the TM5S collaborative robot with the DG-3F-M articulated gripper. Unlike traditional parallel grippers that rely on simple open-and-close movements, the DG-3F-M uses three articulated fingers that adapt to the shape of the object being handled. | Feature | DG-3F-M Capability | | Pinching Payload | 2.5 kg rated (5 kg maximum) | | Enveloping Payload | 10 kg rated (15 kg maximum) | | Grasping Method | Shape-adaptive articulated fingers | | Application Focus | High-mix, low-volume production | This design allows the robotic system to handle randomly oriented components, irregular parts, mixed product batches, and objects with varying geometries. As a result, manufacturers can reduce dependence on specialized fixtures and minimize the need for frequent process redesigns. Why does this matter? Manufacturers increasingly require automation systems that can adapt to changing production demands. Adaptive gripping technology helps bridge the gap between robotic efficiency and operational flexibility, making articulated robots more practical for modern manufacturing environments. Why are high-mix production environments creating new opportunities? Manufacturers today increasingly operate in high-mix, low-volume production environments where product variations change frequently. This trend is driven by growing customer demand for customization and shorter product life cycles. Traditional automation systems often struggle in such environments because production lines require frequent adjustments, fixtures must be replaced regularly, and setup times can increase significantly. These limitations reduce operational flexibility and can diminish the economic benefits of automation. The Techman Robot-Tesollo solution demonstrates how articulated robot systems can address these challenges through adaptive grasping and collaborative automation. By accommodating a wider range of product shapes and configurations, these systems can support more agile production strategies. Potential applications include automotive manufacturing, where robots may handle multiple component types during assembly; electronics production, where parts often vary in size and geometry; bin-picking operations involving irregular objects; and mixed-part assembly environments that require continuous adaptability. What could shape the future of articulated robots? Current developments suggest that the future of articulated robots will be shaped by a combination of artificial intelligence, advanced automation, and broader deployment opportunities. The growing integration of AI-driven robotics is expected to improve robot autonomy and adaptability, while laboratory automation continues to emerge as a promising application area. At the same time, investments in humanoid robotics, mobile manipulators, and adaptive gripping technologies indicate that the robotics ecosystem is becoming increasingly interconnected. Collaborative robot platforms are also likely to play a larger role as organizations seek automation solutions that can operate alongside human workers. LG CNS's continued investment strategy and research initiatives indicate growing industry confidence in intelligent robotic systems capable of supporting long-term robot transformation programs. Leading companies driving innovation in the Articulated Robot industry. The articulated robot industry is characterized by the presence of several established automation and robotics companies, including ABB Ltd, FANUC Corporation, KUKA, Yaskawa Electric Corporation, Kawasaki Heavy Industries, Ltd., Adept Technology Pvt. Ltd., American Robot Corporation, Rockwell Automation, Inc., Honeywell International Inc., and Omron Adept Technology, among others. To strengthen their market position and expand their customer base, these companies are increasingly focusing on product launches and technological advancements as key growth strategies across global markets. Such initiatives enable them to enhance their robotics portfolios, address evolving industrial automation requirements, and maintain a competitive edge within the articulated robot industry. Next steps. Organizations evaluating articulated robot investments should consider: * Assessing high-mix production requirements. * Identifying repetitive precision-driven workflows. * Evaluating AI-enabled automation capabilities. * Exploring collaborative robot and adaptive gripper combinations. * Developing long-term robot transformation roadmaps. Conclusion. Articulated robot technology is entering a new phase of industrial relevance. Recent developments from LG CNS, Techman Robot, and Tesollo demonstrate that modern robotic systems are evolving beyond traditional automation toward intelligent, adaptive, and highly flexible operational platforms. As physical AI, collaborative robotics, and adaptive gripping technologies mature, articulated robots are becoming strategic tools for organizations seeking greater efficiency, precision, and resilience across manufacturing, logistics, and laboratory environments. For business leaders planning future automation investments, these developments represent important indicators of where industrial robotics is heading.

Recently Posted Jobs

Sign up to get curated job recommendations

Dexmate is Hiring for 40 Jobs on Simplify!

Find jobs on Simplify and start your career today

Don't see your dream role? Check out thousands of other roles on Simplify.Browse all jobs