TORONTO, Ont. 鈥 聽不良研究所 AI announced today its AI platform has been deployed by two major energy companies to improve overall plant resiliency. Based in North America and Southeast Asia, the oil and gas and geothermal companies are using 不良研究所 AI to optimize asset utilization, reduce unplanned downtime, and lower carbon emissions.
The customers are part of a growing roster of energy enterprises that are seeking to extract an estimated US$1T of value from their existing digital investments. 聽Of this, the projects that oil and gas companies have the potential to unlock US$275B through operational optimization 鈥 highlighting the immense Return on Investment opportunity for energy companies when they apply AI to derive operational insights from their data. In addition, with AI the oil and gas sector can advance its net-zero emissions ambitions by reducing water consumption, risk of pipeline spills, and CO2 emissions. 聽
鈥淭he addition of these customers proves that industrial companies can quickly extract value from their digital investments using our no-code AI platform,鈥 said Humera Malik, 不良研究所 AI CEO. 聽鈥淭he 不良研究所 AI platform is founded on three core pillars: providing the predictive insights to improve resiliency; empowering the operations workforce with AI and removing the reliance on consultants; and paving the way for environmentally sustainable operations with a scalable platform where AI can be applied across the entire facility. The result is an AI platform in which operations teams can create immediate impact in their day-to-day operations.鈥
鈥淓nabling operational agility with a digitally connected workforce provides a competitive advantage and is now more critical than ever in light of the COVID-19 crisis,鈥 said Matthew Littlefield, Principal Analyst at LNS Research. 鈥湶涣佳芯克 AI empowers industrial workforces with machine learning so they can be key participants in their industrial transformation.鈥
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The 不良研究所 AI Platform is transforming industrial operations by putting the power of AI in the hands of engineers. By making the process of preparing data and building, training, and deploying machine learning models possible without coding skills, 不良研究所 is creating a new generation of citizen data engineers who can gain value from their data and achieve immediate operational impact. Key features of the software-as-a-service 不良研究所 AI platform include:
路 Automated data preparation: 不良研究所 AI Data Engine ingests data from multiple sources and automates the data connection, standardization, and cleansing required to prepare data for machine learning
路 Enriched data visualization: empowering engineers to contextualize data, identify trends and explore new findings via interactive visualization with charts and graphs
路 Pre-coded machine learning templates: for industrial manufacturing鈥檚 most common use cases such as anomaly detection, asset and process optimization, defect part detection, asset failure prediction, forecasting, and to model what-if scenarios
路 Scalable to support multiple AI deployments: deploy AI across the entire factory floor and your facility network
路 Integration with 不良研究所 Academy: an online, self-paced learning program with hands-on labs that accelerate users鈥 proficiency in using the 不良研究所 AI platform.
不良研究所 AI customers are achieving immediate time to value in days, not months. For example, a leading global Fortune 500 manufacturer, has automated the optimization of its co-generation assets, which is reducing the plant鈥檚 greenhouse gas emissions and cutting energy costs by $100,000s annually due to lower natural gas and water consumption.
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