Rapidly developing technologies are transforming the way major transportation assets are managed. Innovations such as the cloud, cognitive analytics, the industrial internet of things (IIoT), and advanced cybersecurity are showing emergent signs of improving operations of afloat, ashore, subsurface, and aloft transportation assets. In the maritime space, shipowners, operators, technical managers, OEMs of shipboard machinery, and associated regulatory entities are embracing these technologies in order to better understand the overall health of their machinery.
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Use Case: Preventing Customer Churn for Retail Banks
As competition, banks are expected to lose revenue due to customer churn. Natural language processing and automated machine learning generate insights into why customers churn and how to retain them.
Use Case: Predicting Financial Market Regimes with AI
The ability to more accurately predict market volatility, price changes, and price change directions comes with AI. To find the best possible methodology, one investment and trading company staged an
Customer Success Story: Improving Refinery Safety and Efficiency with AI at the Edge
Leading contract manufacturer, Texmark Chemicals Inc., has historically monitored their equipment manually and at high cost. Facing increasing costs and additional safety liabilities from this...
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Neuroevolution amplifies a data scientist's work by enabling more effective model building, providing the ability to rapidly iterate through thousands of different models and architectures.
Use Case: Optimizing Energy Trading with Machine Learning
Utilities need to accurately forecast pricing for whole sales and retail markets to provide competitive offerings. Machine learning solutions allow utilities to move beyond the traditional approach.
Use Case: Improving Grid Reliability and Resiliency
The utility sector has already benefited from the use of machine learning by implementing predictive maintenance that predicts failures on critical equipment well in advance.
Maximizing Offshore Oil Well Production
AI is being adopted rapidly in the oil and gas industry due to the significant operational efficiencies it provides to operators through advanced analytics for predictive and prescriptive maintenance.
Use Case: Alternative Data for Investment Management
From hedge fund managers to mutual funds and even private equity managers, alternative data has the power to improve valuation of securities and boost the clarity of the investment process.
Reimagine Offshore Maintenance with AI
The oil and gas industry is a dynamic, ever changing arena. SparkCognition has developed AI-based predictive and prescriptive maintenance solutions to help companies adapt to the age of digitization.
Customer Success Story: Optimizing Aerospace Maintenance with NLP
Customer Success Story: Identifying Vane Failure From Combustion Turbine Data
Combustion turbines are the central power-producing asset in a combined-cycle power plant. When a unique combustion turbine vane failure led to a two-month outage and $30M in lost opportunities...
Customer Success Story: Identifying Non-Productive Time and Invisible Lost Time on Oil Rigs
Non-productive time is a great enemy for oil and gas operators. E&P operators need to better categorize and analyze rig activities to track and eliminate non-productive time and invisible lost time.
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Customer Success Story: KYC Process Automation for Banking
How Patented Machine Learning Techniques Predict and Prevent Future Cyber Attacks
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Case Study: Improving Offshore Production with AI-Based Predictive Analytics
One major oil platform operator was facing recurring failures in production subcomponents that resulted in >10% downtime and millions of dollars of lost production. They employed SparkCognition’s turn
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