Predict asset failures across generation, transmission, and distribution systems to reduce costs and maximize uptime. C3.ai Predictive Maintenance uses supervised and unsupervised machine learning algorithms to analyze streaming data across sensor, SCADA, and asset management systems, as well as technician notes and weather, to detect anomalies and predict malfunctions before they occur.
Improve utility program effectiveness, increase customer engagement, and enable new products and services by providing a 360-degree view of customers and proactively identifying accounts at risk (e.g., call center, low CSAT) or most likely to participate in critical initiatives. C3.ai Customer Insight uses machine learning-based customer segmentation models that analyze data from internal customer systems (e.g., CRM, billing) and external sources (e.g., demographic) to deliver actionable customer insights for more effective targeting and richer engagement.
Empower customers to reduce energy costs and improve building operations through real-time tracking, analytics, and optimization. C3.ai Energy Management uses machine learning techniques to enable accurate forecasting, benchmarking, building optimization, demand response, and anomaly detection to lower costs, improve building operations, and meet utilities’ and their customers’ shared energy-efficiency goals.
Proactively identify instances of energy theft to protect core revenues, at higher accuracy and lower cost than conventional rules-based approaches. C3.ai Fraud Detection uses supervised machine learning algorithms to correlate disparate enterprise systems and high-frequency transactions to pinpoint fraudulent activity and support advanced pipeline management for efficient resolution and revenue recovery.
Reduce operating expenses associated with AMI and other IoT sensor deployments by identifying and predicting sensor and network health issues. C3.ai Sensor Health uses supervised and unsupervised machine learning techniques to prioritize meters projected to malfunction and enable a managed workflow for efficient triage and resolution of issues.
Guided and regular maintenance inspections, provide information related to the inspections, location-based content, and time record of tasks carried out in the application.
Created to encourage learning and training environment, easy introduction process, and provide safety instructions.
Visualization of piping and wiring through the walls.
Allow the real-time visualization of loT sensor devices with machine learning, production status monitoring, and device AR control.