Skyline Robotics is revolutionizing the traditional practice of window washing through innovative technology that aims to redefine the industry. The startup’s window-washing robot, Ozmo, is currently operational in Tel Aviv and New York, and has successfully cleaned major Manhattan buildings in partnership with Platinum, the city’s largest commercial window cleaner, and real estate giant The Durst Organization.
Ozmo is a machine that hangs from the side of a high-rise building. It utilizes a robotic arm with a brush to clean windows, guided by instructions from a LiDAR camera that maps the 3D environment using laser technology. The camera accurately identifies the parameters of the windows by mapping the building’s exterior.
According to Ross Blum, the chief operating officer and founder, although Ozmo is currently controlled by a human operator on top of the building, it has the potential to be operated remotely from various locations around the world. Blum stated, “That person, other than regulation, doesn’t actually have to be there for our sake. We could, in theory, remote-control Ozmo from different parts of the world.”
The name “Ozmo” comes from the fact that the machine utilizes reverse osmosis to remove contaminants from the water, resulting in a more efficient cleaning process. Blum highlighted that there is no need for separate squeegees and brushes to achieve a perfectly clean window; Ozmo’s cleaning motion accomplishes it all.
Currently, the cost of the Ozmo is around $500,000, but Skyline Robotics board member and Platinum CEO James Halpin explains that building owners can expect a three-to-five-year payback on their investment.
Moving away from the specifics of Ozmo, it is worth noting that this machine reflects a broader trend of technology replicating human work. Artificial intelligence innovations, such as ChatGPT, have recently raised concerns about employment vulnerabilities in various industries, including customer service, writing, and computer programming.
The World Economic Forum predicts that by 2025, approximately 85 million jobs will be displaced due to automation, but 97 million jobs requiring reskilling and retraining will emerge. A 2016 study from the Brookings Institution reveals that maintenance and construction jobs, including window washing, have a medium share of tasks (30% to 70%) that are susceptible to automation.
Platinum’s Halpin supports Ozmo because of the shortage of workers in the high-rise window washing field. He emphasized, “Currently, we are experiencing a labor shortage in all real blue-collar fields in New York City. We could hire another 20% just to keep up with the current work that we have at this point.”
Both Halpin and Blum maintain that their goal is not to replace human workers, but rather to retrain and reassign window washers to operate the technology. Logistically, Ozmo reduces the number of people needed to clean a building from a team of three to four window washers to just one operator.
However, there are concerns among some window washers like Jose Nieves, who has been in the industry for 23 years and works at Rockefeller Center. Nieves believes that the dangers of window washing are often exaggerated and argues for the preservation of human labor. Represented by the SEIU 32BJ, Nieves emphasized that cutting costs on the backs of workers is not the right approach.
Futurists like Aleksandra Przegalińska from Harvard’s Labor and Worklife Program study the collaboration between humans and robots and explore how machines can handle tedious or dangerous tasks. While it is still early to fully evaluate Ozmo’s impact, Przegalińska finds the opportunity to shift human labor away from risky fields appealing. She cited the example of machines being deployed during the pandemic to deliver medication to infected patients.
Skyline Robotics has been developing Ozmo since 2017 and has secured $6.5 million in pre-Series A funding, as well as a grant from the Israeli government. The company is dedicated to advancing the capabilities and adoption of this innovative window-washing robot.
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