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Veea and Conxai Fuse Edge Computing, Connectivity, and AI Technology

With a common mission to transform the global construction industry using AI-driven network edge solutions designed to make worksites safer, more efficient, and manageable, Veea Inc., an innovation leader in integrated smart edge connectivity, computing, and security, announced a joint effort with CONXAI Technologies GmbH, a technology start-up that puts AI capabilities into the hands of users without writing a single line of code.

CONXAI’s industry-first modular no-code AI platform applies AI-based techniques to job-site imaging and sensor data collected by the Veea Edge Platform, extracting information and synthesizing knowledge to reveal opportunities for operational and safety improvements.

According to McKinsey, the global construction industry is valued at over $12 trillion, is highly inefficient and among the least digitalized among all sectors. Over the past twenty years, McKinsey says, there has been only 1% productivity gains, which costs the world $1.6 trillion in waste based on the gap.

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PREDICTIONS-SERIES-2022

The construction industry has historically been slow to adopt disruptive digital solutions. Recently, however, leading construction companies have recognized that the worksite is a prime candidate for reaping the benefits of AI solutions to increase efficiency, quality, and safety. They have begun to adopt AI for a variety of use cases, including optimizing manual labor, while also making management simpler when it comes to routine, yet essential tasks.

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CONXAI has selected the Veea Edge Platform to support jobsites due to its flexibility and speed in deployment, making it easy to establish a local communications and computation capability at the worksite, while increasing system responsiveness and reducing bandwidth to, and reliance on the cloud. The resulting monitoring, management, and maintenance solution is designed to improve safety, reduce risks, improve expensive machinery management efficiency, and provide remote access to information in real time. The platform also enables users to create and simulate cognitive digital twins of their jobsites and spot deviations from plan, design, and best practices early on.

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“The upside opportunity for real estate developers and the construction companies they hire is limitless, especially as nearly every asset can be instrumented with increasingly low-cost sensors and camera systems.” said William Hurley, Chief Revenue Officer, Veea. “With Veea’s edge computing platform and mesh networking, we can collect and analyze data locally while supporting automated systems and providing data in real time to jobsite managers that can improve safety and productivity. We can also ship data to multiple clouds, feed existing enterprise systems, and enable remote management, which is extremely valuable to large, distributed construction companies. CONXAI’s advanced ‘no-code’ AI solutions are intuitive and appreciated by the IT teams who support digital transformation initiatives. We are honored to have been selected to work with CONXAI on these creative and commercially valuable solutions.”

“AI is the construction industry’s greatest opportunity for improvement of safety, quality and productivity,” said Sharique Husain, CEO and Co-Founder, CONXAI. “By empowering the construction industry with No-Code AI, we are accelerating a widespread adoption of “data-driven operations” in the construction industry and closing the productivity gap. For solutions to work consistently in real time, while supporting mission critical programs, we sought an innovative collaboration partner who could remove many of the adoption barriers that traditional edge computing solutions would face in the dynamic construction site environment. Veea’s platform, including connectivity, computation, security, and management services were the natural choice. CONXAI’s AI simply works best when supported by a world-class edge and communications infrastructure.”

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[To share your insights with us, please write to sghosh@martechseries.com]

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