Use cases energy intensive industries
Leveraging human & artificial intelligence to turn raw industrial data into new energy & CO2 savings
Use cases energy intensive industries
Integration of downstream value chain (audit, action plan) in a disruptive web software based on data-driven machine learning. - Strict focus on industrial process optimisation with high barriers to entry. - Software functions aligned with ISO 50001 certification requirements. - Interoperability and big data cross-analysis of energy, production and maintenance information systems. - Financial independence from historic market players. - Disruptive business model based on SaaS recurrent fees. -
Industrial manufacturers lack energy competitiveness resulting in high energy bills. Operational teams cannot easily manage this problem as they lack relevant key performance indicator (KPI) analytical means, even though data is all around them!
Energiency helps industrial companies save energy thanks to machine learning and predictive analytics that continuously scan data related to energy and fluids. Data is available in relation to production, maintenance and weather conditions.
• 20% energy savings without additional investments.
• Competitive.
Leveraging human & artificial intelligence to turn raw industrial data into new energy & CO2 savings
Use cases energy intensive industries
The example of Hénaff shows that the energy revolution is possible for industrial producers.
Success Story Henaff Energiency ENG
Energiency was chosen by SKF for its expertise in AI and Data Science, its capacity for operational implementation of statistical predictions, and for the quality of its support.
Success Story SKS Energiency ENG
