Eugenie provides an emissions intelligence platform that integrates IoT data with real-time satellite emissions data to identify inefficiencies in asset-heavy manufacturing processes. This technology enables manufacturers to track emissions at the machine level, leading to measurable reductions in carbon output and operational waste.
Funding
$2M 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.
FIFGFPAFounders
Product
Problem
Asset-heavy manufacturing processes often lack granular visibility into emissions and operational inefficiencies, hindering efforts to reduce carbon output and improve overall productivity. Traditional methods rely heavily on lagging indicators and aggregated data, making it difficult to pinpoint the source of emissions and identify specific areas for optimization. This lack of real-time, machine-level insights limits the ability of manufacturers to make informed decisions and implement effective sustainability initiatives.
Solution
Eugenie provides an emissions intelligence platform that combines IoT sensor data with real-time satellite emissions data to deliver machine-level insights into manufacturing processes. The platform's AI-powered digital twin technology enables manufacturers to track, trace, and reduce emissions by identifying anomalies and opportunities for optimization. By integrating data from multiple sources, Eugenie provides a comprehensive view of asset performance, process control, and emissions tracking. This allows manufacturers to quickly identify and prioritize issues, leading to improved efficiency, reduced waste, and lower carbon footprints. The platform's explainable AI framework simplifies the interpretation of insights, making it easy for operations and maintenance staff to take action.
Target Audience
Eugenie primarily targets manufacturers in asset-heavy industries such as metals & mining, oil & gas, chemicals, cement, steel, and semiconductor & electronics, who are seeking to improve sustainability, boost productivity, and achieve operational efficiency.
Features
- Integration of IoT sensor data with real-time satellite emissions data
- AI-powered digital twins for anomaly detection and optimization
- Machine-level emissions tracking and process monitoring
- Multi-sensor network augmentation, merging data from satellites, drones, and IoT devices
- Explainable AI framework for effortless interpretation of insights
- Real-time advisory views of processes and asset status
- User-friendly graphical representation for decision support