ivBOT provides an AI‑driven platform that consolidates data from solar, wind and other renewable assets—including SCADA, IoT sensors, weather forecasts and market signals—to deliver continuous performance intelligence. Its real‑time anomaly detection, adaptive generation forecasting, and automated optimization recommendations help operators, asset managers and investors monitor, predict and improve portfolio output through interactive dashboards and API integration.
Funding
Funding not disclosed
Founders
Product
Problem
Energy producers and investors struggle to obtain real-time, actionable insights from disparate renewable asset data, leading to suboptimal performance monitoring, forecasting, and risk management.
Solution
IvBOT offers an AI-driven platform that aggregates and analyzes data from solar, wind, and other renewable installations to deliver continuous performance intelligence. The system ingests sensor feeds, weather forecasts, and market signals, applying machine‑learning models to detect anomalies, predict output, and optimize asset operation. Users access dashboards that visualize key metrics, forecast generation, and recommend corrective actions, enabling more efficient asset management and informed investment decisions.
Target Audience
Primary customers are renewable energy operators, asset managers, and investors seeking data-driven performance monitoring and optimization for solar and wind portfolios.
Features
- Unified data integration layer for SCADA, IoT sensors, and external weather APIs
- Real-time anomaly detection using predictive machine‑learning algorithms
- Generation forecasting with adaptive models that incorporate market and weather dynamics
- Automated optimization recommendations for curtailment, maintenance scheduling, and performance tuning
- Interactive dashboards with customizable KPIs, trend visualizations, and alerting mechanisms
- API access for embedding analytics into existing enterprise systems