Powering the
Energy Transition
Cotan Energy delivers domain-specific machine learning models for oil & gas infrastructure, renewable asset optimization, and smart grid balancing.
Purpose-Built for Energy Infrastructure
Deploy secure, scalable AI models directly into your existing SCADA and cloud environments.
Oil & Gas Production
AI-driven monitoring for gas production facilities, pipeline integrity, and predictive maintenance for heavy machinery.
View PlatformRenewable Assets
Maximize yield with computer vision for solar arrays and predictive yaw optimization for wind turbines.
View PlatformSmart Grid & Storage
Dynamic load forecasting, automated grid balancing, and battery lifecycle optimization algorithms.
View Platform
AI Monitoring for
Gas Production
Transform raw SCADA and sensor data into predictive intelligence. Our specialized models identify microscopic anomalies before they escalate into facility shutdowns.
Predictive Compressor Maintenance
Acoustic and vibration ML models predict centrifugal and reciprocating compressor failures weeks in advance.
Computer Vision Leak Detection
Integrates with existing optical gas imaging (OGI) cameras to automatically detect and quantify fugitive emissions in real-time.
Automated Flare Optimization
AI dynamically adjusts steam-to-vent gas ratios, ensuring smokeless flaring while minimizing steam waste and regulatory fines.
Maximize Yield with Predictive Automation
Weather is chaotic; your energy generation shouldn't be. Leverage hyper-local weather forecasting and computer vision to extract every megawatt from your renewable assets.
Wind Farm Wake Steering
AI continuously adjusts the yaw of upwind turbines to redirect wake profiles, preventing downwind energy loss and increasing overall park yield.
Solar Irradiance Forecasting
Combines satellite imagery with cloud-tracking ML to predict short-term drops in solar irradiance, allowing seamless grid battery intervention.
Drone Vision Analytics
Automated analysis of thermal drone imagery to instantly identify micro-cracks, diode failures, and soiling on massive solar arrays.
Dynamic Load Balancing for the Modern Grid
As distributed energy resources (DERs) and EV charging destabilize traditional grid architectures, Cotan AI provides the predictive intelligence required to maintain frequency and prevent outages.
Hyper-Accurate Load Forecasting
Deep learning models ingest weather data, historical consumption, and real-time events to predict localized demand spikes with 98% accuracy.
BESS Lifecycle Optimization
Maximize the ROI of grid-scale batteries. AI determines the optimal depth of discharge based on market pricing and battery degradation models.
EV Fleet Integration
Coordinate charging schedules for commercial EV fleets to occur during off-peak hours or periods of high renewable generation.