Opti: AI 에너지 어드바이저 for 빌딩

In homes or small buildings, it is difficult to easily understand or manage power consumption, and related information is scattered across dashboards or in technical terms, making it difficult for non-experts to practice energy savings. This has led to unnecessary energy waste and high electricity bill penalties during peak hours.

Existing energy management methods rely on expensive equipment upgrades or expert consulting, making them realistically difficult to apply to homes and small buildings.

Opti uses AI to analyze real-time power data collected from existing smart meters without additional hardware, providing users with insights in the form of natural language queries and responses. For example, if you ask, "How can I reduce electricity bills during peak hours?" the AI chatbot will suggest specific reduction measures.

By combining generative AI and simulation models, it recommends energy-saving measures tailored to each building and evaluates the effects of introducing solar panels or batteries. Unlike competing solutions, even ordinary people without specialized knowledge can easily optimize energy use in natural language, and it achieves practical innovation in that it can be implemented with software alone without separate equipment investment.

The adopters of Opti are general consumers (B2C) who want to reduce energy costs, such as individual households or owners/managers of small and medium-sized buildings. Rather than professional energy managers or large corporations, the main customer base is home and commercial building operators without specialized energy management personnel.

In the future, there may be B2B collaboration with energy service companies, but initially, it is expected to be a model where consumers subscribe directly or receive it in partnership with power companies.

This solution can be applied regardless of country or region as long as there is a smart power metering infrastructure, so it has high global scalability. The entry barriers in terms of policy/regulation are also relatively low, and we are already seeking to enter overseas markets with the CES Innovation Award as an opportunity.

In addition, by utilizing the collected energy data, it can be expanded to the B2G/B2B area, such as smart city energy management or carbon neutrality policy support, and has the potential to develop into a business linked to building energy efficiency services and demand response (DR) projects. In short, it is a solution that is not tied to a specific country or industry and can be applied across a wide range of building sectors.

The CES Innovation Award was given in recognition of Opti's practicality and completeness. It received attention by winning the Innovation Award in the Smart Communities category for "easily solving complex energy data with AI."

Experts highly appreciate the automation of areas that previously required advice from energy experts based on chatbots, and are looking forward to the extent of cost savings that can be achieved in actual use. On the other hand, it is pointed out that user participation is key because user behavior changes according to AI recommendations must be accompanied, and localization is necessary according to differences in electricity rate structures and data accessibility in each country.

Overall, positive evaluations such as "a practical example of combining AI with energy saving" are the mainstream, and the atmosphere is closer to appropriate evaluation than overestimation.