Augury Acquires Process-Based AI Company Seebo, Targets $1 Trillion in Untapped Capacity for Manufacturers and Industry

Augury, the leading provider of IoT and Industrial AI solutions that improve health and reliability of machines for manufacturing and industry, announced it has signed a definitive agreement to acquire Seebo, a leader in AI-based process intelligence. The deal is a combination of cash and stock and is valued between $100 million and $200 million.

Augury’s Machine Health solutions help companies ranging from Colgate and PepsiCo to ICL and Essity predict machine reliability and performance issues to eliminate downtime and increase production efficiencies. Seebo’s Process-Based Artificial Intelligence provides manufacturing teams with the insights to optimize processes in the face of multiple, often-conflicting objectives such as improving quality, throughput and yield while reducing waste, energy consumption and emissions.

Together the companies will provide a never-before possible, AI-driven view into the interplays between the diverse factors that influence overall production health. These correlated insights will enable customers to take actions that improve asset performance, process optimization, quality, sustainability and safety.

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“Manufacturers realize their competitiveness depends on empowering their frontline teams. However, methodologies like TPM and IWS can only drive production gains so far, without accurate insights into the inter-related ways that processes, materials, environment and equipment impact production health,” said Saar Yoskovitz, CEO of Augury. “The lack of a unified platform to provide these insights stifles collaboration and progress. The combination of our full-stack machine health platform and Seebo’s process-based AI will give cross functional teams the correlated view they need to transform how they work, and unlock $1 trillion in untapped production potential from existing facilities worldwide.”

Some of the world’s leading manufacturers and industrial companies are already making strides on this journey, and see the combination of machine health and process health as foundational to their long-term objectives:

“We’ve applied Augury’s Machine Health Solutions to reduce downtime and increase capacity as a foundation of our digital transformation. Our next goal is the integration of those machine-level insights with other variables, from product mix to environmental or process changes, that let us control quality, yield and efficiency in ways we can’t today,” said Warren Pruitt, VP Global Engineering Services at Colgate-Palmolive. “We see the combination of capabilities that Augury and Seebo are working to bring together as exactly the right approach to helping us maximize production health and achieve our other goals around sustainability, workforce engagement and profitability.”

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Scott Reed, SVP of Service Operations at GAF, said, “The building materials industry is working to maximize production to meet global demand for construction, and to do so in more sustainable ways than ever. GAF has ambitious goals on both those fronts, and we see greater adoption of the kinds of AI driven technologies Augury is pioneering as crucial to our efforts and those of our industry. By getting greater insight across our materials, processes and equipment we can increase capacity, reduce waste, maintain quality and stay aligned to our business metrics all at the same time. That’s something that’s been very hard to do in the past.”

“Production health, a combination of machine health and process health, allows industrial companies to embrace digital transformation more holistically,” said Michael Guilfoyle, Vice President, Energy Transition and Industrial Sustainability at ARC Advisory Group. “With this acquisition, Augury now provides AI-driven production health, delivering a path for its customers to extend the optimization of their existing production processes. The potential for value is significant, mainly through the ability to integrate previously siloed work groups and their key use cases to greater effect, from improved uptime and emissions reduction to greater yield improvement and quality assurance.”

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