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Algorized Joins MassRobotics to Accelerate the Future of People-Sensing in Robotics

ALGORIZED

News provided by

Algorized

Apr 29, 2025, 12:24 ET

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CAMPBELL, Calif., April 29, 2025 /PRNewswire/ -- Algorized, a deep tech startup innovating people-sensing AI through its multimodal sensor fusion engine, has joined the prestigious MassRobotics startup community to redefine the future of human-machine interaction.

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Algorized Joins MassRobotics
Algorized Joins MassRobotics

As a resident startup of MassRobotics—the leading innovation hub for robotics and automation—Algorized joins a global community of robotics leaders, OEMs, and deep tech innovators who are shaping the next generation of intelligent systems. This collaboration provides a platform to accelerate product development, expand pilot programs, and partner with industry leaders at the intersection of automation and human presence.

"Joining MassRobotics reinforces Algorized's mission to design people-sensing AI for safer, more efficient collaboration between humans and machines," said Natalya Lopareva, CEO of Algorized. "We're building an AI multimodal sensor fusion engine for real-time people detection and vital signs monitoring in challenging environments, such as industrial floors where humans interact with robots. This technology is transforming how machines perceive and respond to the human environment." 

"We are thrilled to welcome Algorized to the MassRobotics community," said Colleen Anderson, Director of Community & Events at MassRobotics. "Their journey from Switzerland to California and now to Boston is a testament to the global reach and collaborative spirit that MassRobotics supports. Their presence strengthens the diversity of cutting-edge robotics and sensing technologies being developed by startups in our ecosystem, and we look forward to supporting their continued growth and impact."

Algorized's sensor-agnostic edge platform can be deployed on any existing UWB and mmWave radar sensor. This enables scalable solutions for intelligent automation across manufacturing, logistics, automotive, and smart infrastructure.

Live Demos at Robotics Summit 2025

Algorized will debut its latest advancements at Robotics Summit 2025 in Boston, showcasing live demos of its people-sensing AI in Booth #354, Startup Alley.

Attendees will experience:

  • Real-time human detection, including body movement tracking
  • Contactless vital sign monitoring, capturing breathing and heart rate without wearables
  • Edge AI decision-making, enabling adaptive and context-aware responses for safe human-robot interaction

The summit will also feature insights from Algorized on the future real-time human positioning, industrial safety intelligence, and integrated fusion sensing for collaborative automation.

About Algorized

Founded on extensive academic research, Algorized enables groundbreaking sensing and positioning applications through a software-only upgrade to existing commodity sensors. The platform leverages proprietary machine learning algorithms to access a wealth of data from UWB radar and wireless sensors, facilitating real-time positioning and vital sign detection in any environment. The company is pioneering innovative solutions for sectors ranging from automotive to human-machine interaction in robotics. Visit Algorized for more information. 

About MassRobotics

MassRobotics is the world's largest independent robotics hub dedicated to accelerating robotics innovation, commercialization and adoption. Our mission is to help create and scale the next generation of successful robotics and Physical AI technology companies by providing entrepreneurs and startups with the workspace, resources, programming and connections they need to develop, prototype, test and commercialize their products and solutions. While MassRobotics originated and is headquartered in Boston, we are reaching and supporting robotics acceleration and adoption globally and are working with startups, academia, industry and governments both domestically and internationally. Learn more here.

CONTACT: Megan Liu, [email protected]

SOURCE Algorized

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