ClearBlade, an IoT platform and edge AI company, launched the forecasting AI component within its intelligent assets application, enabling real-time prediction of asset behavior using historical and live data without requiring advanced technical expertise.
The solution enables users to forecast future equipment conditions, resource requirements, and operational risk by embedding ML models within operational processes.
Forecasting AI operates at the edge, ensuring predictions can function even in connectivity challenges, and offers a user-friendly no-code interface for business and operational staff.
“We developed Forecasting AI to empower operational teams to plan ahead without relying on a centralized analytics team,” explains Eric Simone, CEO of ClearBlade. “By integrating forecasting directly into Intelligent Assets, we’re assisting customers in achieving tangible ROI, rather than merely experimenting with AI.”
Key applications include predictive maintenance, intelligent energy management, facility optimization, fleet monitoring, utility planning, and inventory/supply chain predictions.
The component seamlessly integrates with ClearBlade’s digital twin platform, requiring no external system or infrastructure modifications. It runs on Google Cloud’s Vertex AI, BigQuery, and Gemini models, delivering robust intelligence in an enterprise-grade package.
This marks ClearBlade’s third AI Component, joining Anomaly Detection and Intelligent Video Analytics, to offer modular, edge-friendly AI solutions.
Related
AI/ML | ClearBlade | digital twin | edge AI | IIoT
