Delfosim offers a unified SaaS platform for renewable energy operators that aggregates real‑time data from wind, solar, hydro, and battery storage assets and applies AI‑driven predictive models and physics‑based digital twins to forecast failures and optimize performance. The solution provides customizable dashboards, an Event Manager for automatic issue classification, and component‑level loss analysis, helping operators improve asset availability, reduce downtime, and lower maintenance costs.
Funding
$6.9M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
2OCVFounders
Product
Problem
Renewable energy operators often rely on fragmented data sources and manual analysis to monitor wind, solar, hydro, and battery storage assets, leading to delayed fault detection, suboptimal performance, and increased downtime.
Solution
Delfos provides a unified SaaS platform that aggregates real-time data from diverse renewable assets and applies machine‑learning and physics‑based digital twin models to predict failures and optimize performance. The system offers customizable dashboards, an Event Manager that classifies operational issues, and detailed loss analysis for each component. Predictive analytics proactively identify underperformance, enabling operators to schedule maintenance before outages occur. Integrated modules cover wind turbine subsystems, solar strings and inverters, hydro generators, and battery storage metrics such as SoC, DoD, and RTE. The platform consolidates data across vendors, delivering actionable insights that improve asset availability and revenue while reducing maintenance costs.
Target Audience
Primary customers are operators and asset managers of wind farms, solar parks, hydro power stations, and battery energy storage systems seeking data‑driven performance and reliability solutions.
Features
- Real‑time data ingestion from multiple renewable sources with unified visualisation and KPI tracking
- AI‑driven predictive models and physics‑based digital twins for early fault detection and performance optimization
- Event Manager that automatically identifies, classifies, and prioritizes operational issues
- Component‑level loss analysis for wind (gearbox, yaw, pitch, etc.), solar (strings, inverters, pyranometers), hydro (stator, rotor, bearings), and BESS (SoC, DoD, SoH, cycles)
- Power curve assessment and detailed energy loss reporting across the entire asset portfolio
- Customizable dashboards and alerts that integrate with existing O&M workflows
- Scalable SaaS architecture supporting small and large installations, from single turbines to multi‑GW portfolios