New Industry 4.0 technology, specific to process manufacturing, increases accuracy and accessibility of predictive insights into downtime and quality issues.

TEL AVIV, November 15, 2018 – Seebo today announced the launch of its unique process-based artificial intelligence (AI)  technology. The new AI-based capabilities for production line data introduce unmatched accuracy and ease of use of the company’s predictive quality, predictive maintenance and production line intelligence solutions.

Process manufacturers today face rising demands on production capacity and continuous disruptions that affect uptime, quality, and throughput. Increasingly, they are turning to machine-generated data to investigate and solve their production line problems. But finding meaningful insights entails applying sophisticated machine learning technologies to a carefully engineered big data repository – a process beyond the technical and financial reach of most manufacturers.

Seebo’s new process-based AI addresses these issues by incorporating the production line process flows, together with OT and IT data, into machine learning algorithms and digital twin visualization for more accurate and accessible intelligence about line disruptions.

Production teams can then use Seebo’s predictive quality and maintenance solutions to mitigate future disruptions, without mastering data science.

“For the first time, AI-powered Industrial IoT is accessible to any process manufacturer with costly downtime and quality problems, “said Lior Akavia, Seebo CEO. “An effective Industry 4.0 solution must include a vast amount of contextual information – specific production process flows, batch recipes, and quality test results, to name a few. Translating that data into predictive insights that users can trust entails lengthy, expensive and high risk projects which businesses today can’t tolerate.

“With our new process-based  AI, Seebo solutions can now be implemented to deliver value in weeks, not months or years. It’s Industrial AI, democratized.”

Manufacturers in the food & beverage, chemicals, energy, paper milling, and other process manufacturing verticals use Seebo’s process-based AI for production line intelligence: setting production KPIs, tracking them on a hierarchical digital twin of the production line, and navigating through the digital twin to determine root causes of issues.  

Seebo’s process-based AI automatically detects “golden batch” recipes and machine settings in the production line, and alerts on meaningful deviations from the golden batches. Correlated events and predictive insights provide supportive data into imminent disruptions. Production line teams – from process engineers to floor operators – can then implement automated recommendations that increase production uptime and prevent costly quality defects.

The company has clients already using the new capabilities, and expects to leverage its process-based AI to increase growth through its existing solutions.

About Seebo

Seebo utilizes an Industry 4.0 SaaS Platform to provide predictive quality, predictive maintenance and production line intelligence solutions for industrial manufacturers.

Customers infuse their production line processes and knowhow, together with data from OT and IT systems, into machine learning – without requiring the customer to master data science.  The result: Predictive Quality, Predictive Maintenance, and Condition Monitoring solutions with unmatched accuracy and simplicity.

The Seebo Industrial IoT Platform combines visual, code-free tools for Process and Data Modeling, Automated Root Cause Analysis, Predictive Analytics and Digital Twin Visualization. These tools enable the company to tailor solutions to clients’ specific needs, and to easily adapt the solutions post deployment.

Manufacturers across industries – including Grundfos, Stanley, Procter & Gamble, Ralph Lauren, and many more – use Seebo to increase overall equipment effectiveness (OEE), minimize maintenance costs, and continually improve quality.

Founded in 2012, the company has raised over $22M from top VC firms, and was named a Gartner Cool Vendor in the Internet of Things for 2017.