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Sustainable solutions. For tomorrow.

NeroTech: Real-time AI insights drive energy efficiency and emission mitigation

NeroTech is an AI-driven energy-saving software that provides exceptional flexibility and customization options, enabling users to manage multiple building systems and equipment through a centralized interface. By implementing NeroTech software, building owners can achieve increased energy efficiency, cost savings, and a reduced environmental impact. NeroTech enables companies to manage and improve their ESG (environmental, social, and governance) performance with advanced machine learning, natural language processing (NLP), and generative AI techniques. Customers can utilize NeroTech to unify and store disparate ESG data, automate reporting to standards, boost the specificity and traceability of carbon emissions calculations, track stakeholder ESG priorities, and manage ESG plans with scenario analysis.

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Real-time data, value interpretation

Data presented,
carbon reduction results at a glance

Ai assistant real-time reporting, communication 

The Value of NeroTech Energy Management

NeroTech Energy Management Solution

Pain Point

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Inability to measure progress toward sustainability goals

Automated measurement and verification through machine learning allows for accurate tracking against cost and sustainability goals

Time-consuming manual calculations of sustainability project results

Automated AI/ML project savings measurement and validation to track sustainability ROI at the equipment and facility level

Limited collaboration between sustainability and operations teams in identifying project opportunities

Artificial intelligence-based alerts and recommendations to identify specific operational opportunities with estimated sustainability impact

Existing systems are rigid, closed, and not scalable

The flexible, secure and open platform provides robust integration and full interoperability with all enterprise and off-enterprise systems (e.g., historian systems, torch stack sensors, PEMS, CEMS).

Inability to track the carbon footprint of products and leverage sustainability investments

Industry-specific data models and out-of-the-box emission factor libraries enable advanced product carbon footprint analysis

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