S

Standard Bots

Designs and manufactures AI-native industrial robots

Electronics Manufacturing Engineer

Full-Time
$110k - $145k/yr+ Employee Stock Options
Mid
Bachelor's, Associate's
Glen Cove, NY, USA
HybridThree days on-site per week required.
Manufacturing & Process EngineeringManufacturing Engineering

About the job

Requirements
  • An Associate's or Bachelor's degree in Electrical Engineering Technology, Electrical Engineering, or Manufacturing Engineering, or a related field; equivalent hands-on experience is also accepted.
  • At least 4 years of experience in electronics or PCBA manufacturing engineering, including hands-on ownership of an SMT line and its processes such as paste, placement, reflow, AOI, and rework.
  • Demonstrated DFM/DFA expertise, including reviewing real PCB designs, providing feedback to electrical engineers, and identifying boards improved by catching problems before release.
  • Fluency with IPC standards, including IPC-A-610, IPC-7351, IPC-2221, and J-STD-001.
  • Ability to read and interpret schematics, PCB layouts, fabrication and assembly drawings, BOMs, and stack-ups, and identify problems or omissions in release packages.
  • Hands-on command of SMT processes, including reflow profiling, stencil and paste, placement, SPI/AOI, and rework, with the ability to diagnose tombstoning, bridging, voiding, head-in-pillow, and similar defects.
  • Hands-on experience with DFM-check tooling such as Valor, CAM350, Allegro DFM, or equivalent, and ability to run rule-based checks against layout and fabrication/assembly data.
  • Design-for-test fluency, including designing in test coverage and access and reviewing boards for testability through test points, ICT, flying probe, and boundary scan.
  • Hands-on electrical test and measurement experience with oscilloscopes, multimeters, and bench instruments, including running hardware-team-defined tests and defining test procedures.
  • Experience preparing and reviewing manufacturing output packages for handoff to internal production lines or external contract manufacturers.
  • A constructive, direct communication style that enables explaining design problems to engineers, supporting the rationale, and securing fixes.
Responsibilities
  • Review PCBA layouts, footprints, stack-ups, and fabrication/assembly packages before release, including stack-up and controlled-impedance manufacturability; provide specific DFM/DFA and design-for-test feedback to electrical engineers, identify issues and rule violations, and drive resolution before build.
  • Run systematic, rule-based DFM/DFA checks using automated tools such as Valor, CAM350, Allegro DFM, or equivalent, and maintain rule decks as parts, processes, and vendors change.
  • Partner with electrical engineering to build test coverage and access into designs, including test points, probe access, and ICT, flying-probe, and boundary-scan considerations.
  • Own and uphold the DFM rule set for component spacing, courtyards and keep-outs, panelization, fiducials, thermal relief, testability, and land-pattern standards; document and maintain standards and ensure designs conform.
  • Ensure manufacturing output packages—including Gerbers, fabrication and assembly drawings, BOM, pick-and-place data, and stack-up—are complete, unambiguous, and manufacturable by internal lines or external contract manufacturers before release.
  • Own SMT/PCBA process engineering for the in-house line, including stencil and paste, placement, reflow profiling, SPI and AOI, and rework; drive process control, first-pass yield, and defect reduction, and own changeovers and new-board bring-up.
  • Bring up, verify, and debug boards on the bench using oscilloscopes, multimeters, and lab instruments; run hardware-team-specified tests, define test procedures, and help establish automated/functional test as production scales.
  • Partner with electrical engineering through NPI, from prototype builds to repeatable volume, and close the loop between design intent and manufacturability on the production floor.
  • Connect electrical engineering with the production floor by translating design intent into build- and test-ready instructions and feeding yield, defect, and test data back to design.
  • Serve as the manufacturing-engineering interface to external contract manufacturers by qualifying processes, resolving DFM findings, reviewing first articles, and holding CMs to the quality bar.
  • Perform root-cause analysis of solder and assembly defects using 8D and 5-Whys, reduce scrap and rework, and feed lessons learned into DFM standards.
Desired Qualifications
  • ECAD fluency in Altium, Cadence/Allegro, KiCad, or equivalent sufficient to open designs, inspect footprints and layout, and mark them up.
  • Experience standing up or scaling an in-house SMT line, or transitioning boards between internal and contract manufacturing.
  • Depth with CAM/DFM tooling such as Valor, CAM350, and Allegro DFM, including experience building or maintaining automated DFM rule decks.
  • Automated/functional test experience, including National Instruments/LabVIEW, Pico Technology, or equivalent.
  • Background in robotics, automotive, aerospace, medical, or other precision/high-reliability electronics.
  • Lean/Six Sigma and SPC experience on an SMT line.
  • Familiarity with ERP/MES and PLM systems.

About the company

S

Standard Bots

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cbWebsite

Standard Bots designs and manufactures AI-native industrial robot arms and humanoids that learn tasks by demonstration rather than traditional programming. It builds its own actuators and other hardware in the U.S., delivering end-to-end hardware and software for tasks such as machining, welding, palletizing, grinding, fastening, dispensing, assembly, and inspection. The company differentiates itself with in-house actuation, U.S. manufacturing, and an AI-driven, demonstration-based programming approach to provide a scalable automation platform at lower prices than legacy industrial robots. Its goal is to expand U.S. manufacturing, capture a sizable share of domestic robot deployments, and accelerate AI-native product development with funding support.

Company Size

51-200

Company Stage

Series C

Total Funding

$287M

Headquarters

Glen Cove, New York

Founded

2016

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Simplify's Take

What believers are saying

  • June 2026 Series C valued Standard Bots at $1 billion, funding 70,000-square-foot expansion.
  • June 24, 2026 Roboflow partnership shortens vision deployment from files to minutes.
  • Standard Bots says it is on pace for 10% of new U.S. robot deployments.

What critics are saying

  • The June 2026 $200 million expansion demands flawless factory ramp and hiring execution.
  • ABB, Universal Robots, and legacy incumbents already own installed bases and service networks.
  • If demonstration-trained robots underperform in production, Standard Bots loses trust, contracts, and valuation.

What makes Standard Bots unique

  • Standard Bots vertically integrates U.S. robot manufacturing in Glen Cove, New York.
  • Its robots are taught by demonstration, not code, compressing deployment from months.
  • Roboflow and Cognibotics integrations deepen its no-code physical-AI stack in 2026.

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Benefits

  • Health Insurance
  • Dental Insurance
  • Vision Insurance
  • Life Insurance
  • Disability Insurance
  • 401(k) Company Match
  • Employee Stock Options
  • Paid Vacation

Growth & Insights and Company News

Headcount

6 month growth

0%

1 year growth

-3%

2 year growth

-1%
Vialynx Inc
Oct 16th, 2026
Standard Bots: the 90% programming claim.

Standard Bots: the 90% programming claim. Standard Bots launched chat-based robot programming on October 15. The 90% time cut is a company claim, not a measured result. Standard Bots launched three AI skills for its industrial robot arms on October 15, 2026. Agent is a chat interface that builds a program from a plain-language description. Locate lets an operator tap a part on the camera feed, or describe it, and the arm finds and tracks it. Inspect trains a vision model on a shop's own parts and flags defects such as scratches. The company says Locate cuts programming time by 90 percent. That is a product launch and a company figure. It is not an independent measurement of how long a program takes, or of how often a chat-built routine runs a shift without a human stepping in. What the October 15 launch actually records. The launch is a software layer on robots Standard Bots already sells. Agent is a chat trained on the company's manuals and best practices. An operator asks for a machine-tending routine. The software asks about the cell. It builds the program with the operator. Locate replaces a grid of hand-taught waypoints with a tap or a text description. Inspect, built with Roboflow, lets a shop train a model on photos the robot takes, or load a model of its own. The 90 percent figure is attached to Locate. Standard Bots says eliminating the waypoint grid is what produces the cut. The figure is not broken out by task, by shop size, or by how many programs were timed. A 90 percent reduction in programming time is a large claim. A claim without a baseline, a sample, and a definition of "programming time" cannot be checked. Forbes reported the figure as the company's. ASSEMBLY reported it the same way. Neither published a stopwatch. The company names customers including Sunoco, Lockheed Martin, NASA, and the U.S. Army, and says it serves small businesses in almost every state. A customer list is not a deployment count. The company has also said it is on pace to do 10 percent of new U.S. industrial robot deployments. That is an ambition the company stated earlier in the year, not a 2026 audited share. A private company can be on pace for a number it does not have to file. What a chat interface does not settle. Programming an industrial arm is not writing a sentence. A routine has to clear fixtures, respect joint limits, stop when a person enters the cell, and recover when a part is not where the camera expected it. A chat that builds the routine can shorten the first draft. It does not, by itself, say whether the draft is safe, or whether it runs a full shift. The 90 percent claim is about programming time, not about cycle time or scrap. A shop that spends an hour instead of ten setting up a changeover has saved setup. If the resulting program is slower, or drops parts, the savings can disappear in production. The launch materials do not report a cycle-time comparison or a scrap rate. This is a different claim from an open humanoid that a lab can test. RoboParty's RP1 was a hardware platform with a published interface. Standard Bots is a commercial arm with a new programming layer, and the performance number is the vendor's. It is also different from a surgical system with a regulated workflow. The da Vinci 5 coverage dealt with a device that has a clearance path. A machine-shop arm does not. A chat-built program that fails on a factory floor fails on a part, a fixture, or a person. The company does not publish a price for the AI skills, a failure rate, or a safety certification tied to the chat interface. Those absences are the gap between a launch and a specification. What would make the claim testable. Three records are still open. First, a timed comparison. Programming time for the same task, with and without Locate, on a named cell, with a sample larger than an anecdote. The October 15 materials do not include one. Second, a production number. How many chat-built routines have run a full shift without a human intervening, and what the scrap rate was. A launch demo is not a shift. Third, a price and a safety note. What the skills cost, and what stops the arm if the chat builds a path that is wrong. The company page describes the skills. It does not price them or name a safety standard they satisfy. Until those exist, October 15 is a software launch: a chat that builds routines, a tap that finds parts, and a vision check, with a 90 percent programming-time figure that the company states and no one else has measured. The counterargument. The generous reading is that the bottleneck in a small shop is the integrator, not the arm. A 12-person machine shop cannot hire a robotics programmer for every changeover. A chat that asks about the cell and a tap that finds the part are the right shape of tool for that shop, even if the 90 percent is a ceiling the company hopes to hit. The customer list includes names that buy industrial equipment for a reason. Shipping a programming layer that a frontline worker can use is a product, and the company is careful enough, in the coverage, that the 90 percent is presented as its own claim. That reading holds as a product thesis. It does not make the 90 percent a measurement. The October 15 launch opens a chat window on a robot. It does not close the question of how long the program takes, or how often it runs. Frequently asked questions. What did Standard Bots launch on October 15, 2026? Three AI skills: Agent, a chat that builds robot programs from plain language; Locate, which finds and tracks parts from a camera tap or a text description; and Inspect, a vision check trained on a shop's own parts. What is the 90 percent figure? A company claim that Locate cuts programming time by 90 percent by replacing a grid of hand-taught waypoints. No independent measurement, baseline, or sample size is published. Who uses the robots? The company names Sunoco, Lockheed Martin, NASA, and the U.S. Army, and says it serves small businesses widely. That is a customer list, not a deployment count. Is there a price or a safety standard for the skills? Not in the launch materials. The company describes the skills. It does not price them or name a safety certification for the chat interface. What is missing? A timed comparison, a production scrap or uptime figure for chat-built routines, and a price. Related reading. Sources. This article is for informational purposes only and does not constitute investment, legal, or financial advice. WeeklyReviewer is an independent publication. Readers should conduct their own due diligence before making any investment or business decision. Editor & Lead Journalist · WeeklyReviewer Mahim Gupta is the editor and lead journalist at WeeklyReviewer. With a research-first philosophy and a commitment to verified, unbiased reporting, Mahim delivers deep-dive investigations and product reviews that go well beyond the headline. His work spans technology, geopolitics, finance, and product culture - always with an eye on the underlying systems that shape our world. Follow this topic in live news.

Rocking Robots
Oct 16th, 2026
Standard Bots enables factory workers to program robots using AI.

Standard Bots enables factory workers to program robots using AI. Industrial robot manufacturer Standard Bots has introduced an AI-based programming platform designed to allow factory workers to configure and modify robotic tasks without writing code. Using an iPad, operators can describe what they want a robot to do, demonstrate movements or identify objects through a camera interface. The system then generates robot routines that can be adjusted by workers without requiring specialist programming knowledge. The platform is intended to make industrial robots easier to operate in manufacturing environments where companies may not have dedicated robotics engineers or programmers. Traditionally, configuring an industrial robot requires operators to define movements, positions and sequences, often with assistance from specialist system integrators. Standard Bots aims to reduce that dependency by allowing employees on the factory floor to create and modify routines themselves. The system combines three functions, called Agent, Locate and Inspect, which address different aspects of robot programming, object recognition and quality control. According to Standard Bots, these functions can be operated through an iPad interface, allowing workers to set up robotic tasks without writing software code. Programming robots through natural language. The Agent function allows operators to describe a task in ordinary language rather than writing programming instructions. For example, a worker can ask the system to create a machine-tending routine. The AI then asks questions about the production setup and generates the corresponding robot program. The conversational interface is trained on Standard Bots' documentation and programming practices. Workers can use it to develop new routines or make adjustments when production requirements change. The company says this approach allows employees without previous robotics experience to participate directly in programming and operating automated equipment. A second function, Locate, uses computer vision to identify objects and determine their positions. Instead of manually programming individual robot coordinates and movement points, an operator can select an object in the robot's video feed or describe it in text. The system then identifies the object and uses its position to guide robotic movements. This capability is particularly relevant for manufacturers handling different products or frequently changing production batches. Conventional robotic systems often require new programming or mechanical adjustments when the position or type of a component changes. Standard Bots says Locate can reduce the programming time associated with these adjustments by up to 90%. That figure is a company claim, and independent performance data has not been provided. Workers can also configure automated inspections. The third function, Inspect, extends the platform to quality control. Developed in cooperation with computer vision company Roboflow, it allows operators to integrate custom vision models into robotic routines. These models can be trained to identify defects in manufactured components, including surface scratches. During an inspection, the robot scans a component and flags detected defects. Depending on the configured routine, the system can refer the result to a worker or initiate a programmed response. Operators can load their own inspection models into the platform, rather than relying exclusively on models supplied by Standard Bots. The company is also developing foundation models for robotic applications. Reducing dependence on specialist robot programmers. Standard Bots is positioning the platform for manufacturers that want to introduce automation without relying on external specialists for every programming change. This is particularly relevant to smaller manufacturers, where workers frequently perform multiple production and maintenance roles. The company cites research from the National Association of Manufacturers indicating that nearly 200,000 of the approximately 240,000 manufacturing companies in the United States have fewer than 20 employees. Such businesses may have limited resources for dedicated robotics engineering. According to Evan Beard, co-founder and CEO of Standard Bots, the objective is to allow manufacturing workers to automate tasks by describing the required actions or demonstrating them directly to a robot. The company also argues that simpler programming could make robotic automation more practical in high-mix manufacturing, where production lines regularly switch between different components. In these environments, the time required to reprogram robots can affect the economic case for automation. Path Machining Automation, a contract machining company in the Minneapolis-St. Paul area, is among the businesses using Standard Bots technology. Its president and CEO, Adrian Nistler, says the programming interface has shortened development work and made robotic systems easier to configure. The broader technical change is that robot programming is moving beyond manually defining every movement and coordinate. By combining language-based instructions, computer vision and task-specific AI models, Standard Bots is seeking to give production workers more direct control over automation. How reliably these capabilities perform across different industrial environments, and how much specialist support remains necessary for deployment and safety validation, will depend on the application.

Robotics & Automation News
Oct 1st, 2026
Runway moves into robotics with open-weight Praxis-1 AI model.

Runway moves into robotics with open-weight Praxis-1 AI model. Discover more Source Suppliers Rent Machinery Build Robots Runway, one of the best-known developers of generative AI video technology, is moving into robotics with Praxis-1, an open-weight AI model designed to use knowledge learned from video to control physical robots. "Open-weight" means developers can download the model and run or adapt it themselves, rather than only accessing it through Runway's servers. The company describes Praxis-1 as its first "world action model" and says it is based on the same large-scale video pretraining underlying its general world models. Runway is currently testing Praxis-1 with robotics companies Noble Machines, Standard Bots and Ultra Robotics on several types of robot hardware. It plans to make the model publicly available in the coming months. The move takes Runway beyond its established generative video business and into the rapidly developing physical AI and robotics market. Discover more Automation Consulting Service Industrial Robot Sales AI Software Development Runway says: "Today Robotics & Automation News is announcing Praxis-1, its first open-weight world action model. It's built on the same large-scale video pretraining behind its general world models. "We're actively testing Praxis-1 with early partners across a variety of embodiments, and will release it publicly in the coming months." Using internet video to train robots. The central idea behind Praxis-1 is that robots do not necessarily need to learn predominantly from enormous quantities of robot-generated training data. Collecting real-world robotics data is expensive and time-consuming, particularly when it requires robots to be teleoperated through tasks repeatedly. Runway instead wants to exploit the vastly larger quantities of ordinary video available for training AI models. Video can teach a model about object behavior, movement, physical interactions and how humans perform tasks. Runway's argument is that a robot policy beginning with this understanding of the physical world has an advantage over one trained primarily from robot action data. The company says: "A policy that already understands physical plausibility and object behavior from video pretraining has an enormous head start on one built from action data alone." Runway compares the approach with the development of large language models, which acquire a broad understanding of language from large quantities of text before being adapted for more specific tasks. The company says its experiments indicate a similar scaling effect in robotics, with robot policy performance improving as the amount of third-person video used during training increases. Web video approaches robot training data. One experiment presented by Runway compares policies pretrained using ordinary web video with those pretrained using teleoperated robot video. After fine-tuning, the company reports a final placement error of 16.1 cm for the model initially trained on web video, compared with 16.0 cm for the model trained using teleoperated robot footage. Runway notes that the difference is not statistically significant within the reported uncertainty. The company is also testing Praxis-1 on more difficult manipulation problems involving cluttered environments, transparent objects, deformable materials and groups of similar-looking objects. In another demonstration, Runway shows the same policy operating in both a controlled studio environment and a domestic kitchen without retraining. Runway brings world models into robotics. Praxis-1 builds on Runway's development of interactive video and world models including Solaris and GWM Worlds 2. These models attempt to represent how environments and objects change over time rather than simply generating individual images or predetermined video sequences. Runway says: "By teaching our models how to generate accurate physics - how objects behave, how hands move, what a task looks like partway through - we've created dynamic, complex environments for agent training in the digital and physical world." Praxis-1 applies that approach to robotics, with Runway aiming to develop a general-purpose policy capable of working across different robot embodiments and environments. The company also says previous experiments found that simulating robot policies inside its world model produced results with a 0.95 correlation to subsequent real-world performance. Testing on three different robot platforms. Praxis-1 is being tested with three early robotics partners. Noble Machines is evaluating the model for bimanual manipulation, while Standard Bots is running it on its RO1 six-degree-of-freedom robotic arm. Ultra is testing Praxis-1 with a mobile robotic platform. Runway says the early-access program will be expanded to additional companies ahead of the model's public release. The testing program is intended to evaluate both performance and safety across different robot configurations and operating environments. Praxis-1 will be released with open weights. Runway also plans to make Praxis-1 available with open weights rather than restricting access to a proprietary hosted model. The company links that decision partly to its view that greater interoperability between AI models and robot hardware will be important as physical AI develops. Runway says: "We view open world models as a compounding advantage that gives hardware developers flexibility and control they don't currently have." The company is currently accepting applications from robotics developers interested in testing Praxis-1 on their hardware before its wider release. The launch puts Runway into an increasingly important area of AI research: using large-scale world models and knowledge acquired from video to train machines capable of interacting with the physical world. If the approach scales, the significance of Praxis-1 may lie in reducing one of robotics' persistent bottlenecks - obtaining enough diverse real-world training data to produce robots that can operate reliably outside tightly controlled environments.

Roboflow
Jun 24th, 2026
Roboflow and Standard Bots Partner to Bring Custom Visual Intelligence to Every Robot.

Roboflow and Standard Bots Partner to Bring Custom Visual Intelligence to Every Robot. Standard Bots customers who build vision systems in Roboflow can run them on their robots, uniting two of the leaders in physical AI behind a single, seamless journey from what a robot sees to what it does. CHICAGO, June 24, 2026 - Roboflow and Standard Bots are announcing a partnership to enable robots to see, understand, and act with visual intelligence. Standard Bots customers who train vision models in Roboflow can now deploy those models to their robot to spot a defect, recognize a specific part, count items, read a label, or watch a zone, without needing an engineer to transfer files or configure the robot. Bringing visual intelligence to industrial robots allows them to learn new vision skills the same way you'd teach anyone on a factory floor: hold up a part, give it a few examples, and it learns to recognize it. From then on, the robot sees, decides, and acts on its own. The robot that used to execute one motion can now adapt to inspect for defects, sort good from bad, guide its own picking and palletizing, and adapt to the world in front of it. The two companies unveiled the partnership this week at Automate 2026, the largest automation event in North America. Visit the Roboflow booth (#21015) or Standard Bots booth (#736) to see live demonstrations of industrial robots running custom vision models to see, decide, and act in real time. Making physical AI accessible to every business. Vision and motion have always been the two halves of a robot that can do real work. This partnership delivers that connection as a seamless product experience for manufacturers of all sizes. For manufacturers who train their own vision models in Roboflow, deploying them to a robot has historically required engineer time, SSH access, and manual file transfers. This integration removes that barrier by bringing Roboflow-trained models into the robot's skill library with the same ease as any other task. When custom model deployment is this simple, a manufacturer can get a new product online in weeks instead of quarters. Robots bought for one task can be taught a second, and a third, because adapting it is now a matter of showing it something new, rather than rebuilding it. Robots that can learn from visual data change the economics of automation with faster payback, and a machine that is worth more the longer it runs. "Standard Bots makes robots that anyone can teach. We make it easy for machines to see and understand the world," said Joseph Nelson, co-founder and CEO of Roboflow. "Put those together and you get something the factory floor has been waiting for: a robot you can point at a problem and trust to handle it. Every camera and every robot in a facility becomes programmable, by the people who actually run the line." "Our mission is to put a capable robot to work in every American factory, and the robots that win are the ones that are easy to use," said Evan Beard, CEO of Standard Bots. "Our robots are built to be taught, not just programmed. For manufacturers who use Roboflow for annotation and training, this integration means going from a trained model to a deployed robot skill in minutes - and sending data back to keep improving. That's the kind of seamless workflow that changes what's possible on the factory floor." To schedule a tailored demonstration based on your business needs, contact Roboflow, Inc. here. About Roboflow Roboflow gives organizations the platform to build visual intelligence that understands and acts in the physical world. The Roboflow platform spans labeling, training, deployment, and applications, and is used by more than one million engineers and over half of the Fortune 100 across manufacturing, logistics, rail, defense, healthcare, retail, and sport. Learn more at roboflow.com. About Standard Bots Standard Bots is America's largest AI-native industrial robot manufacturer, designing and assembling its six-axis robots in Glen Cove, New York. Built to be more affordable and easier to use than legacy systems, Standard Bots robots are trusted by Fortune 500s and independent shops alike to automate machine tending, palletizing, welding, inspection, and more. Learn more at standardbots.com. Cite this post. Use the following entry to cite this post in your research: Trevor Lynn. (Jun 24, 2026). Roboflow and Standard Bots Partner to Bring Custom Visual Intelligence to Every Robot. Roboflow Blog: https://blog.roboflow.com/roboflow-and-standard-bots-partner-to-bring-custom-visual-intelligence-to-every-robot/ Stay Connected Get the Latest in Computer Vision First Trevor Lynn Trevor leads Marketing at Roboflow. He focuses on sharing insights from Roboflow customers to inspire the broader AI community and help advance visual AI. Topics.

Citybiz
Jun 11th, 2026
GiantLeap Capital backs Standard Bots in $200 million Series C round.

GiantLeap Capital backs Standard Bots in $200 million Series C round. June 11, 2026 As manufacturers face mounting pressure to increase productivity, strengthen domestic supply chains, and address labor shortages, industrial robotics is becoming a strategic priority across sectors ranging from aerospace and defense to automotive and logistics. GiantLeap Capital has announced a strategic investment in Standard Bots, the New York-based robotics company that describes itself as America's largest manufacturer of AI-native industrial robots. The investment is part of Standard Bots' recently announced $200 million Series C financing, which valued the company at $1 billion. The funding round attracted participation from a group of technology and industrial investors, including General Catalyst, the Amazon Industrial Innovation Fund, Samsung Next, RoboStrategy (Nasdaq: BOT), and other existing institutional backers. For GiantLeap Capital, the investment aligns with its strategy of supporting companies operating at the intersection of artificial intelligence, advanced manufacturing, aerospace, defense, and critical infrastructure. The firm views robotics as an increasingly important technology for enhancing industrial capacity and economic competitiveness as manufacturers seek more efficient ways to automate production. Standard Bots has developed AI-native robotic systems that can be trained through demonstration rather than conventional programming methods. The approach is designed to reduce deployment complexity and enable manufacturers to automate a broader range of tasks across production environments. The technology is being applied across industries including aerospace, defense, automotive, energy, logistics, and industrial manufacturing. The company has already deployed robotic systems at hundreds of manufacturing facilities across the United States. Customers include Lockheed Martin, NASA, and the U.S. Army, highlighting the growing adoption of advanced automation technologies within both commercial and government sectors. According to the company, it is on track to account for approximately 10% of new industrial robot deployments in the United States next year, a figure that reflects the increasing demand for AI-powered automation as manufacturers modernize operations. "We are entering a decade in which manufacturing output, industrial resilience, and national competitiveness will increasingly be determined by software, AI, and robotic density rather than labor arbitrage," said Samir Parikh, Founder and Managing Partner of GiantLeap Capital. "Standard Bots has built a differentiated AI-native robotics platform that can compress deployment cycles, improve unit economics, and learn continuously from real-world operating data." Parikh added that the firm believes the company has the potential to expand productivity across U.S. industry while strengthening the domestic industrial base that supports both economic growth and national security objectives. The financing is expected to support several growth initiatives, including expanding Standard Bots' manufacturing footprint in the United States, increasing production capacity, accelerating development of its AI technologies, and broadening adoption of robotic systems across additional industrial sectors. Chief Executive Officer and Co-Founder Evan Beard said the company's next phase of growth will require both technological innovation and strategic partnerships capable of supporting large-scale deployment. "Scaling intelligent automation in America requires more than great technology; it requires manufacturing depth, strategic relationships, and partners who understand how to build enduring companies," Beard said. "GiantLeap brings that perspective, along with deep experience across industrial technology, aerospace, and defense." The investment comes as policymakers and industry leaders place renewed focus on domestic manufacturing capabilities amid global competition and ongoing efforts to strengthen supply-chain resilience. Advances in artificial intelligence are enabling a new generation of industrial robots capable of handling more complex workflows, creating opportunities for manufacturers to improve efficiency while addressing workforce challenges. Headquartered in Glen Cove, New York, Standard Bots designs and manufactures its robotic systems in the United States. The company's focus on AI-native automation positions it within a rapidly growing segment of the robotics market, where machine learning and demonstration-based training are helping reduce barriers to industrial automation. GiantLeap Capital is a growth equity firm that invests across private and public markets, focusing on technology-driven businesses with the potential to transform industries at scale. The firm's investment in Standard Bots reflects continued investor interest in robotics companies developing technologies aimed at modernizing industrial operations and expanding manufacturing productivity across the United States.