OptimalAI
applied ai
Energy
Navigate energy transition to optimize operations across the value chain
Optimise supply and demand. Integrate assets and automate demand-side response.
Energy companies worldwide face a myriad of immediate and long term challenges; mounting pressure to reduce greenhouse gas emissions, uneven demand for electricity and hydrocarbons caused by the uncertain recovery from Covid 19 and the ongoing need to upgrade legacy technology and digitalize day-to-day operations. We help energy partners navigate the global energy transition to optimize operations across the value chain.
Reduced Consumption
Reduce national energy usage by up to 10% using deep learning to predict power demand and supply variations using - for instance - weather-related variables and smart meters as exogenous inputs. AI can also be used to briefly switch-off air conditioning at participating businesses as it forecasts peak consumption, easing the load and delaying or forgoing the need to turn on peak generating capacity.
Increased Productivity
Target a 20% energy production increase using machine learning and smart sensors to optimize asset yields.
Predictive Maintenance
Target 10–20% EBIT improvement by using machine learning to enhance predictive maintenance, automate fault prediction and increase capital productivity. AI optimizes the root cause analysis and prediction of infrastructure issues enabling the monitoring and anticipation of failures.
Optimized Pricing
Optimize pricing with time-of-day and dynamic tariffing; match producers and consumers in real time.
Engineers
Allow infrastructure maintenance and optimization to be repeatable and auto-scalable. Seamlessly integrate siloed data to provide engineers with live transparency of total assets and information from across data multiple sources. Enable on-demand analysis to identify opportunities for performance enhancement.
Digital Twins
OptimalAI's digital twins span entire ecosystems to promote effective risk management, resilience and protection against supply chain disruption. We integrate traditionally siloed, cross-domain data into an end-to-end seamless environment enabling live situational awareness and optimal decision-tree predictions.
Optimal Supply Chain
Combining data-driven insights with AI-powered operational network models of the supply chain reduces cost, optimizes capital expenditure and minimizes operational expenses. This can be further enhanced by seamlessly linking IoT connected infrastructure to create real time intelligent supply chains that monitor and predict optimal decision-making.