Full-Time
AI-powered robots autonomously load trailers
$135k - $165k/yr
San Carlos, CA, USA
In Person
Domestic and international travel required up to 20%.
Bachelor's
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Dexterity.ai builds AI-powered robotic systems for logistics and supply chain tasks, with a focus on trailer loading. Its robots autonomously pick parcels and place them into crossbelt or tilt-tray sorters at speeds faster than human workers. The system understands its environment in real time without needing external data feeds or warehouse software integrations, which makes deployment easier across different sites. The company sells the robotic hardware and AI software to businesses and also provides consultation services to help integrate and optimize automation. Dexterity.ai aims to improve operational efficiency and employee safety while making logistics work more attractive to workers, helping customers—from small companies to large enterprises like FedEx—achieve faster, safer, and more scalable parcel handling.
Company Size
51-200
Company Stage
Late Stage VC
Total Funding
$291.2M
Headquarters
Redwood City, California
Founded
2017
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Flexible vacation time
Comprehensive healthcare benefits
Retirement plan
Wellbeing & fitness offerings
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How Beckhoff Automation's EtherCAT and controllers power Dexterity's Mech 'superhumanoid' robot. Safety, communication and motion control components enable smooth operation. Beckhoff Automation Dexterity uses PCB-mounted EJ series EtherCAT I/O terminals in place of traditional wired I/O terminals to minimize Mech's wiring requirements and maximize mass production efficiency. Stay up-to-date with news and resources you need to do your job. Research industry trends, compare companies and get weekly market intelligence with Robotics 24/7. As warehouses become increasingly automated, robotics developers are discovering that artificial intelligence alone isn't enough. Physical AI - the ability for robots to perceive, reason and safely interact with dynamic environments - depends just as much on the automation architecture beneath the surface as it does on advanced algorithms. Dexterity, a provider of physical AI and robotics, selected Beckhoff Automation's PC-based control platform, EtherCAT communication technology and integrated automation ecosystem to power Mech, its industrial "superhumanoid" robot. Designed for physically demanding warehouse tasks such as truck loading, unloading, palletizing and depalletizing, Mech combines dual robotic arms with an autonomous mobile base, requiring real-time communication between motion control, safety systems and AI-driven decision making. The result is a tightly integrated and versatile robotic platform that demonstrates how modern PLC technology and deterministic networking are becoming foundational components of next-generation physical AI. Why Dexterity chose Beckhoff. Dexterity's engineering team wasn't searching for individual automation products - they wanted a unified architecture capable of scaling alongside the company's physical AI platform. Rather than assembling multiple controllers and communication networks, Dexterity adopted Beckhoff's integrated ecosystem built around PC-based control, EtherCAT networking, TwinCAT automation software and TwinSAFE safety technology. "We had two major problems we needed to solve," said David Turney, engineering technical lead at Dexterity. "One, we needed to unify both safety and controls in the same system. And two, we needed to create a scalable product. Part of that is getting rid of terminal blocks and discrete wires by using PCBs. Beckhoff has a portfolio of devices, specifically their EJ modules, which allow us to design a custom PCB using their I/O and safety modules with our custom electronics and cable connectors for the full system harnessing." That decision aligned with Dexterity's long-term product strategy. "Our focus is to create a hardware platform," said Keshav Prasad, SVP of Hardware at Dexterity. "A hardware platform doesn't necessarily mean a single product that does everything. It's a set of modular components that can be put together like Lego blocks." EtherCAT provides the real-time foundation. At the center of Mech's architecture is EtherCAT, Beckhoff's industrial Ethernet communication protocol. EtherCAT enables deterministic communication between controllers, servo drives, I/O modules and safety devices with low latency and virtually no communication jitter. Those characteristics become especially important when coordinating an autonomous mobile robot carrying two independent robot arms operating around people. Mech's ultra-compact rover base moves, spins, and climbs ramps with four steerable wheels. Source: Beckhoff Automation "Some of the Dexterity team, including the founders, had worked with EtherCAT at Stanford," said Doug Schuchart, global intralogistics industry manager at Beckhoff. "EtherCAT was one of the main elements of my conversation with the Dexterity team." Schuchart noted that EtherCAT's openness, communication speed and integrated safety capabilities eliminated many of the limitations associated with traditional fieldbus architectures. "It's the most open and fastest fieldbus protocol in the market," Schuchart said. "Companies like Dexterity don't have to worry about throughput limitations, and it offers incredible bandwidth, which is important for transmitting the sensor data necessary for physical AI." PLC control meets physical AI. While Dexterity's AI software determines how Mech interacts with its environment, Beckhoff's embedded control platform executes the real-time machine control required to safely perform those decisions. Mech uses the compact CX5240 Embedded PC to manage lower-level motion control and safety logic while complementing Dexterity's AI-driven decision-making layer. That separation allows AI to focus on perception and task planning while Beckhoff's PLC platform delivers deterministic execution of motion commands. "We're able to combine the PLC, the motion control, the safety, the navigation for the autonomous vehicle and, in the case of Dexterity, even combine the physical AI analytics into one Beckhoff controller," Schuchart said. "Everything can be executed synchronously instead of having separate controllers with asynchronous communication." That synchronization, according to the companies, improves diagnostics, simplifies lifecycle management and increases overall system performance. It also reduces the physical size of the control components and lowers overall cost. Integrated safety without additional complexity. Warehouse environments introduce unique safety challenges. Mech must safely navigate around people while simultaneously controlling two robotic arms capable of lifting heavy packages inside confined trailers. Rather than separating safety and control networks, Dexterity integrated both over EtherCAT using Functional Safety over EtherCAT (FSoE). "Safety is the core of our system," Turney said. "We made the decision to put safety and controls all in the same network using EtherCAT. That allowed us to have a very flexible system that creates safety from a base layer while allowing much more innovation in the controls." The architecture also simplifies the robot's internal wiring. Because Mech uses safety-rated servo drives connected over EtherCAT, each drive requires only power and network communication instead of additional discrete safety wiring. "Our focus has always been working from the customer's needs," Prasad said. "It's not working in forward motion from technology. We always wanted to do full stack, and we always wanted to make sure that it's a product, not a hard-won experiment or a product that only works in prototypes. But when it came to real production, we didn't have to do a whole redesign. Our strategy was to really think of a full stack, including safety. That's why when you get into the details, you realize how integrated all of these elements are." A partnership built around scalability. Rather than simply supplying hardware, Beckhoff's Special Project Team worked alongside Dexterity engineers during implementation, training and commissioning. "We worked directly with Beckhoff's Special Project Team, and they have world-class support and documentation," Turney said. "There weren't a whole lot of surprises when it came to our development process." Perhaps the most notable aspect of this collaboration is how closely Beckhoff and Dexterity worked throughout development. "The Dexterity team came to us with previous knowledge of EtherCAT and tremendous knowledge of robotics," Schuchart added. "Combined with Beckhoff's knowledge of control systems, mobile robotics and safety, it really brought together a great respect and partnership between the two companies very quickly." As physical AI continues moving beyond warehouses and into broader industrial applications, that combination of deterministic control, integrated safety and scalable automation architecture may prove just as important as the AI models themselves. Tim culverhouse. Editorial Director. Tim is the Editorial Director of Robotics247.com. His mission is to provide valuable information and insights to robotics professionals and decision-makers, and to help them solve business challenges. He is a creative, deadline-driven, and detail-oriented storyteller. In addition, he is a sports broadcaster and public address announcer. Latest in PLCs. Latest in artificial intelligence. Latest robotics news.
Automate 2026: Dexterity, Kawasaki Robotics expand collaboration to scale physical AI for warehouse logistics. RL030N robot arm platform combines Kawasaki's industrial robot engineering, Dexterity's Mech and Foresight World Model. Dexterity and Kawasaki Robotics By Robotics 24/7 Staff June 27, 2026 Dexterity and Kawasaki Robotics Dexterity's Mech robots use the RL030N 8 DoF (degrees of freedom) robot arms for warehouse logistics operations such as trailer loading and trailer unloading. Stay up-to-date with news and resources you need to do your job. Research industry trends, compare companies and get weekly market intelligence with Robotics 24/7. At Automate 2026 in Chicago, Kawasaki Robotics and Dexterity announced an expanded collaboration around Kawasaki Robotics' RL030N 8 DoF robot arm platform and Dexterity's Mech "superhumanoid" robots for warehouse logistics. Mech grows with Kawasaki's robot arms. Dexterity said that it is expanding production and scaling Mech deployments using the RL030N for warehouse logistics applications, including trailer loading and trailer unloading. Dexterity said that Mech's design and warehouse logistics requirements shaped the arm; Kawasaki Robotics and Kawasaki Heavy Industries brought precision engineering and manufacturing expertise to turn those requirements into a production-ready 8 DoF robot arm platform. The companies said that the arm has demonstrated strong reliability in real logistics environments, a critical requirement for warehouse automation at scale. Together, the companies said that they are combing Kawasaki Robotics' industrial robot arm technology with Dexterity's Mech hardware and full physical AI software stack, featuring the Foresight World Model, to support high-throughput warehouse operations where traditional automation has been difficult to scale. Built for warehouse logistics. Dexterity and Kawasaki Robotics said that warehouse logistics is fundamentally different from traditional factory automation. Factories are designed around precision, repeatability, fixed workcells, controlled material flow and minimal unexpected contact. Logistics operations are more variable: packages arrive in different sizes, weights, shapes, orientations and conditions; boxes shift, fall, deform, and stack unpredictably; and contact with packages, containers, conveyors, walls or surrounding equipment is part of normal operation. "Physical AI requires robot arms that combine industrial reliability with dexterity, reach, lightweight construction, and openness to real-time orchestration," said Paul Marcovecchio, director - general industries at Kawasaki Robotics. "Our collaboration with Dexterity has helped sharpen the requirements for AI-driven automation in real warehouse environments." The companies said that Dexterity's Mech design defined the need for a robot arm that is lightweight, dexterous, long-reaching, reliable and robust enough for unavoidable contact. The RL030N 8 DoF robot arm platform adds an articulation axis for confined and variable workflows and is powered by Kawasaki Robotics' open KRNX real-time control API for external AI software, ROS environments and third-party orchestration systems. Dexterity said that it combines the RL030N with Foresight World Model, Mech hardware and its production software stack. "In a warehouse environment, packages vary, boxes move unpredictably, and contact is part of the job. Kawasaki Robotics' RL030N gives Mech the physical foundation for that environment," said Keshav Prasad, SVP of product engineering and operations at Dexterity. "By combining RL030N with Foresight World Model, Mech hardware and Dexterity's production software stack, we can bring physical AI into warehouse operations where traditional automation has not been able to scale." Latest in trailer unloading. Latest in artificial intelligence. Latest Robotics news.
Kawasaki Robotics and Dexterity expand collaboration to scale Physical AI for Warehouse Logistics. RL030N 8 DoF robot arm platform brings together Kawasaki Robotics' industrial robot engineering, Dexterity's Mech hardware, and Foresight World Model Kawasaki Robotics and Dexterity Inc., the enterprise Physical AI company building robots based on proprietary world model for complex industrial work, today announced an expanded collaboration around Kawasaki Robotics' RL030N 8 DoF robot arm platform and Dexterity's Mech super humanoid robots for warehouse logistics. More headlines. Articles. Dexterity is expanding production and scaling deployment of Mechs using the RL030N for warehouse logistics applications including trailer loading and trailer unloading. Dexterity's Mech design and warehouse logistics requirements shaped the arm; Kawasaki Robotics and Kawasaki Heavy Industries brought precision engineering and manufacturing expertise to turn those requirements into a production-ready 8 DoF robot arm platform. The arm has demonstrated strong reliability in real logistics environments, a critical requirement for warehouse automation at scale. Together, the companies combine Kawasaki Robotics' industrial robot arm technology with Dexterity's Mech hardware and full Physical AI software stack, featuring the Foresight World Model, to support high-throughput warehouse operations where traditional automation has been difficult to scale. "Physical AI requires robot arms that combine industrial reliability with dexterity, reach, lightweight construction, and openness to real-time orchestration," said Paul Marcovecchio, Director - General Industries at Kawasaki Robotics. "Our collaboration with Dexterity has helped sharpen the requirements for AI-driven automation in real warehouse environments." Built for Warehouse Logistics Warehouse logistics is fundamentally different from traditional factory automation. Factories are designed around precision, repeatability, fixed workcells, controlled material flow, and minimal unexpected contact. Logistics operations are more variable: packages arrive in different sizes, weights, shapes, orientations, and conditions; boxes shift, fall, deform, and stack unpredictably; and contact with packages, containers, conveyors, walls, or surrounding equipment is part of normal operation. Dexterity's Mech design defined the need for a robot arm that is lightweight, dexterous, long-reaching, reliable, and robust enough for unavoidable contact. The RL030N 8 DoF robot arm platform adds an articulation axis for confined and variable workflows and is powered by Kawasaki Robotics' open KRNX real-time control API for external AI software, ROS environments, and third-party orchestration systems. Dexterity combines the RL030N with Foresight World Model, Mech hardware, and its production software stack. "In a warehouse environment, packages vary, boxes move unpredictably, and contact is part of the job. Kawasaki Robotics' RL030N gives Mech the physical foundation for that environment," said Keshav Prasad, SVP of Product Engineering and Operations at Dexterity. "By combining RL030N with Foresight World Model, Mech hardware, and Dexterity's production software stack, we can bring Physical AI into warehouse operations where traditional automation has not been able to scale." Automate 2026 At Automate 2026, Kawasaki Robotics is showcasing the RL030N as an 8 DoF robot arm platform built for dynamic and confined environments. Together, Kawasaki Robotics and Dexterity are highlighting how advanced robot arms, real-time control interfaces, enterprise Physical AI software, and production-scale Mech systems can unlock new categories of industrial automation. About Kawasaki Robotics A leader in industrial robotics and automation since 1969, Kawasaki Robotics supplies industrial robots and robotic automation systems for a wide range of industries and applications. The company continues to advance industrial robotics through innovations in intelligent inspection, collaborative robotics, real-time control, and autonomous automation systems. Learn more about Kawasaki Robotics here, watch robot application videos here and connect on Twitter, Facebook and LinkedIn. About Dexterity Dexterity Inc. is a Redwood City, California-based robotics company specializing in using Physical AI to give robots human-like dexterity. Dexterity's full-stack technology platform spans AI, world model, software, and hardware and is designed to deliver enterprise-grade operational productivity and safety across logistics, supply chain, parcel, retail, e-commerce, and related industrial workflows. To learn more, visit dexterity.ai.
Kawasaki Robotics and Dexterity have expanded their collaboration around the RL030N 8 DoF robot arm platform for warehouse logistics. Dexterity is scaling production of its Mech super humanoid robots using the RL030N for applications including trailer loading and unloading. The partnership combines Kawasaki Robotics' industrial engineering with Dexterity's Mech hardware and Foresight World Model software. The RL030N was designed specifically for warehouse environments, where packages vary in size and contact with equipment is routine, requiring lightweight construction, dexterity and reliability. The 8 DoF arm features an additional articulation axis for confined workflows and uses Kawasaki's KRNX real-time control API, enabling integration with external AI systems. The collaboration addresses warehouse automation challenges where traditional systems have struggled to scale.
Dexterity.ai has detailed how its production-proven world model, Foresight, is achieving significant performance improvements on NVIDIA hardware as the company scales in enterprise environments. The company showcased the technology at FedEx's 2026 Investor Day in Memphis. Foresight, built from over 100 million autonomous actions in production, gives robots real-time understanding of the physical world. Dexterity's engineering team redesigned the perception pipeline using NVIDIA L4 GPUs and TensorRT, reducing processing time from 1,508 milliseconds to 90 milliseconds per cycle — a 17-fold speedup. The system now processes 32 times more data per cycle. NVIDIA recognised the collaboration at GTC 2026. At the FedEx event, attendees watched Dexterity's dual-armed robot autonomously load a trailer. FedEx discussed plans to scale trailer loading and unloading across several US hubs.