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Skild AI creates a general-purpose artificial intelligence brain for robots. It provides a prefabricated AI model that can be integrated into various general-purpose robots, delivered via an API, to enable high-level decision-making without building custom software from scratch. The product works as a ready-made AI brain embedded in a robotic platform (starting with a mobile manipulator) and exposed through an API so developers and manufacturers can add human-like planning and control capabilities to their robots. This solution differentiates itself by offering a reusable, domain-agnostic AI core for multiple robotics systems rather than bespoke software for each robot, helping to lower development costs and accelerate deployment. Skild AI’s goal is to make robotics development more accessible by supplying the AI brain as a core component to robotics manufacturers and developers who want to build advanced robotic applications quickly and at scale.
Industries
Robotics & Automation
AI & Machine Learning
Company Size
51-200
Company Stage
Series C
Total Funding
$1.8B
Headquarters
Pittsburgh, Pennsylvania
Founded
2023
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Pittsburgh tech powers aviation industry innovation. Homegrown Skild AI partners with PIT to test four-legged robots as part of latest xBridge innovation in the terminal. Already known globally as the robotics capital of the world, the Pittsburgh region is continuing to grow its tech prowess as part of its industry-leading new airport. More headlines. Articles. Pittsburgh International Airport's xBridge innovation program, which has worked with dozens of tech firms from start-ups to national companies, is once again serving as a real-world proving ground for emerging technology. Airport leaders announced two partnerships this week with companies testing cutting-edge products designed to enhance aviation industry efficiency, operations and customer service. Passengers may soon notice four-legged robots, or quadrupeds, strolling through parts of the Airside Terminal supporting terminal operations from monitoring indoor air quality to detecting spills and full trash bins among other uses. The robots, powered by Skild AI's adaptive autonomy software, are being evaluated for their ability to navigate complex airport environments and assist airport operations. Equipped with advanced sensors, cameras and AI-driven perception, the robot can roam autonomously, detect anomalies, and provide real-time data to operations staff. The announcements come as Pittsburgh is hosting the Intelligent Robots & Systems (IROS) Conference 2026, an international event with more than 70 countries represented. "Pittsburgh is a global leader in robotics and AI. Through xBridge, we're creating a place where that innovation can move from the lab into the airport environment and ultimately help shape the future of the industry," said Deepak Nayyar, Executive Vice President and Chief Technology Officer at PIT. "We're looking at how the latest technology can work alongside our staff and airline partners to enhance efficiency, improve operations and provide an additional level of customer service." Up to four autonomous robots and two charging stations will be deployed across the Airside Terminal. Each will have a defined area and keep-out zones. Skild AI will conduct the installation, mapping, supervision, and monitoring. They will also provide on-site training to PIT staff. "As a Pittsburgh company, we're proud to partner with xBridge to make Pittsburgh International a pioneer in airport robotics," said Sara Ahmadi, head of product at Skild AI. "We share the belief that robots will transform how public infrastructure operates, and we're grateful for the confidence they've put in Skild and the energy they bring to making that happen." The project will progress through multiple phases, allowing PIT and Skild AI to evaluate the technology across a range of airport functions. Skild AI was founded in 2023 in Pittsburgh by Deepak Pathak and Abhinav Gupta, both faculty members of Carnegie Mellon University's Robotics Institute and School of Computer Science. Pathak - the Raj Reddy Associate Professor at CMU - serves as chief executive; Gupta serves as president. The company's trajectory has been one of the fastest in the current AI cycle. Backed by SoftBank Group, NVIDIA Ventures, Macquarie Capital (entities administered by Macquarie Capital), Jeff Bezos, Sequoia Capital, Lightspeed, Coatue, Felicis, and others, the company is valued at over $14 billion. Environmental Monitoring The initial use case will focus on mobile indoor air-quality monitoring. Equipped with environmental sensors, a robot will autonomously collect location-specific data, monitor established thresholds and alert airport personnel when readings fall outside defined parameters. By automating routine data collection, the technology could help teams identify potential issues quickly. Supporting Terminal Operations The second phase will explore applications designed to complement the work of custodial and terminal operations teams. Potential use cases include identifying full or nearly full trash bins so employees can prioritize service, detecting potential spills to accelerate response and reduce safety hazards, and monitoring passenger congestion to give operations teams additional visibility into areas experiencing increased crowding. Advanced Applications The third phase will explore more advanced applications, including a potential partnership with BioFlyte, a former xBridge participant, to pair Skild AI's quadruped platform with BioFlyte's airborne biological threat detection technology. The combination could provide mobile biological monitoring beyond fixed sensor locations and give airport personnel another tool for identifying potential threats. The project will also evaluate the potential for autonomous delivery, including food and beverages, to select locations within PIT's airside terminal. If successful, autonomous delivery could also support employees by handling routine point-to-point transportation of items, allowing staff to remain focused on passengers and core operational responsibilities. "Pittsburgh is known globally for its growing tech economy, and our new industry-leading terminal continues to reflect that innovation right at the airport," said Allegheny County Executive Sara Innamorato. "The airport is an economic driver for the region and xBridge is another example of that success." For PIT's airline partners, the project offers an opportunity to explore how autonomous technology could work alongside the people who keep an airport operating efficiently every day. As part of a separate xBridge project, Arrow Analytics, in partnership with Southwest Airlines, is testing its EZ-Board technology in an active terminal environment to explore how the system can improve the boarding process and give airline teams better real-time information on how full overhead bin space is on the flight before a passenger boards. Airlines closely monitor boarding times because even a few minutes can affect aircraft schedules across an entire network. When overhead space becomes constrained, airlines may ask passengers to gate-check carry-on bags. PIT, Southwest Airlines and Arrow Analytics are exploring whether new technology can provide an even more precise, real-time view of carry-on baggage during boarding. Arrow Analytics has developed EZ-Board, an autonomous system that uses off-the-shelf depth cameras and real-time analytics to identify how carry-on bags move through the boarding process. The technology, installed at Gate A7 at PIT, gives airline gate agents and operations teams a real-time picture of baggage volume, while also helping predict how much overhead bin capacity will be needed. "We are excited to work with the innovative team at PIT as we continue to develop our EZ-Board product and computer vision offerings for airports and airlines," said Valerie McNeill, Chief Operating Officer of Arrow Analytics. Providing airline employees with better information about actual baggage volume and projected bin usage could increase boarding speed, reduce uncertainty and support more consistent, data-driven decisions.
Skild AI hit $100M in run-rate revenue selling robots a brain that learns from one video. Europe's Machinery Regulation starts covering machines with self-evolving behaviour on 20 January 2027, and a model that performs tasks absent from its training data is the case it was written around September 10, 2026 - 4:06 pm
Skild AI, a startup developing software that helps robots learn tasks, has reached $100 million in recurring revenue run rate. The company achieved this milestone just 10 months after launching commercial operations. The fast-growing robotics firm's software enables robots to acquire new capabilities more efficiently. This rapid revenue growth demonstrates strong market demand for AI-powered robotic learning solutions.
Can single-video learning solve the biggest obstacle in commercial robotics? Les-Leigh A August 27, 2026 What if a robot could learn to do a job just by watching a ten-second video clip? Skild AI reckons its new S1 foundation model can pull off exactly that, tackling unfamiliar physical tasks without needing a single round of fine-tuning. Built on a large manipulation dataset, S1 adapts on the fly with no retraining, no tedious data collection and no post-deployment calibration required. If these claims survive the real world, it would conquer one of the biggest challenges in commercial robotics. Reprogramming hardware for every new task is slow, eye-wateringly expensive and requires a room full of specialists. A machine that learns simply by watching changes the economics math of it all. What S1 can do (and what still needs proving). At its heart, Skild is showing off one-shot imitation learning straight from video. S1 studies a brief clip of a human or robot doing a task, then builds a custom execution policy without needing any extra training. By pairing visual inputs with natural language context, its video-language architecture figures out what is happening on screen and turns it into real-world robotic movement. Skild released benchmarks showing S1 beating current state-of-the-art models on generalisation tasks, even when faced with workflows completely excluded from its training. The company's demonstrations include manipulation tasks across different object types, lighting conditions and surface textures. CEO Deepak Pathak, who previously led robotics research at Carnegie Mellon and Meta AI, has framed S1 as a step toward robots that can be launched in any environment a human can describe or demonstrate. These results come from Skild's internal testing, which is standard for an early launch, but it does mean independent labs haven't verified the claims just yet. The robotics research community has seen confident one-shot learning announcements before that performed well in curated demonstrations, but less so in the full range of real-world conditions. Transitioning from controlled manipulation benchmarks to active implementations in warehouses, hospital wards or construction sites involves real-world friction. Benchmarks intentionally strip away the unpredictability these real environments require would. Why one-shot learning is A big deal. Traditionally, teaching a robot means gathering hyper-specific data, running heavy supervised or reinforcement learning and locking in a model that only works in one set of conditions. Want to switch tasks? You are starting back at square one. That's why factory robots stick to one assembly line, logistics hardware stays on fixed paths and dynamic automation is wildly expensive for most operators. Large foundation models have shifted the trajectory for language and image processing. By training one large model on varied datasets, it learns broad representations that easily adapt to tasks it wasn't explicitly taught. Skild is now bringing this play to physical robotics: feed S1 enough varied interaction data so that it develops transferable skills, letting it master new workflows through simple demonstrations instead of costly retraining. Dataset scale is everything here. Skild's claim of having the largest manipulation dataset is important, because foundation model generalisation lives and dies by data diversity. Train on a narrow set of tasks, the robot stays narrow. Expose it to a wide spread of hardware types, objects, environments and movement structures - and it actually has something to draw on when facing something new. The real question is whether Skild's dataset is truly rich enough to deliver the seamless adaptability they have promised. The market impact. Reliable one-shot video learning radically lowers both the cost and complexity of hardware implementation. An operator who can teach a machine a new workflow just by filming a quick demonstration opens the door to environments that couldn't previously justify the high setup costs. Small-batch manufacturing, flexible warehouse setups, commercial kitchens and physical retail are all spaces where traditional robotics economics fell flat. The robotics startup space has been building toward this. Physical Intelligence, acquired by Google in late 2024, was working on similar generalisation problems. Figure AI, 1X Technologies and Agility Robotics are all investing heavily in manipulation capabilities. Skild's approach of publishing a foundation model instead of building a specific hardware product positions it differently - as infrastructure for the robotics industry, not just a robotics company itself. For now, S1 is an impressive research showcase. The road from a solid benchmark to a rock-solid industrial release is notoriously long, and the robotics sector is infamous for overpromising on timelines. What makes S1 worth tracking is whether scaling foundation models is the right blueprint for how the problem ultimately gets solved.
Skild AI has raised $1.4 billion in its Series C funding round, bringing its total funding to over $2.2 billion and tripling its valuation to more than $14 billion in seven months. This marks the largest robotics AI funding round in history. The Pittsburgh-based startup, founded in 2023 by Deepak Pathak and Abhinav Gupta, emerged from stealth in July 2024 with a $300 million Series A at a $1.5 billion valuation. The latest round was led by SoftBank, with participation from NVIDIA's NVentures, Bezos Expeditions, Sequoia Capital, LG, Schneider Electric, and Salesforce Ventures. Skild AI develops a hardware-agnostic AI foundation model that can operate across various robotic platforms. The company acquired Zebra Technologies' Robotics Automation business in April 2026 and grew revenue from zero to approximately $30 million within months in 2025.
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Industries
Robotics & Automation
AI & Machine Learning
Company Size
51-200
Company Stage
Series C
Total Funding
$1.8B
Headquarters
Pittsburgh, Pennsylvania
Founded
2023
Find jobs on Simplify and start your career today