1. Overview of the Energy Management Market in ASEAN
1.1. Current Situation of the Energy Management Market:
In the past three decades, cooling demand in ASEAN has grown rapidly. According to IEA 2024, electricity consumption for building cooling reached 80 TWh in 2020, seven times higher than in 1990. Without interventions, this number could reach 300 TWh by 2040, with more than 300 million air conditioners in use.
At the same time, the global energy management system (EMS) market reached USD 35 – 42 billion in 2024 and is forecasted to hit USD 44.6 billion by 2033 (CAGR ~14.5%). This shows a big opportunity for smart energy management system solutions, but it also brings strong pressure for businesses in the region.

1.2. Challenges in Energy Optimization for Businesses
The rapid growth of cooling demand and energy costs creates many problems for ASEAN businesses:
- Rising energy costs: Electricity prices continue to increase, especially in summer, leading to much higher operating expenses.
- Manual operation: In many places, air conditioners are still adjusted based on subjective feelings, causing waste and inefficiency.
- Lack of predictive technology: Traditional systems cannot analyze data in real time, making it difficult to optimize energy for each specific zone.
- ESG pressure: Businesses are required to prove their ability to cut emissions and optimize energy to meet environmental and sustainability regulations.
This reality creates an urgent need for a smart energy management system that can optimize operations, reduce emissions, and deliver long term economic benefits.
2. Leaf AI – AIoT Solution for Smart Energy Management of HVAC (Heating, Ventilation, and Air Conditioning)
2.1 Smart Energy Management System: What is Leaf AI?
Leaf is a smart energy management system for HVAC that uses AIoT technology. It is designed for buildings, factories, retail stores, and offices to automatically control HVAC systems, improve energy efficiency, reduce electricity costs, and cut carbon emissions.

2.2 The Smart Technology Ecosystem of Leaf AI
Leaf AI includes 3 main hardware devices and one software platform:
- Hub (Gateway): Works as the central unit, connecting via Wi-Fi and Bluetooth to synchronize all data. It links sensors and the IR Controller, ensuring the system runs smoothly and continuously.
- Temperature & Humidity Sensor: Installed in occupied areas, this sensor records environmental data every 10 minutes. Accurate information is the basis for AI analysis to adjust cooling/heating for each space.
- IR Controller: Attached directly to air conditioners, allowing remote control of functions such as on/off, heating/cooling mode, fan speed, and air circulation.
- Management Software (Web/Mobile App): A centralized platform where users can control multiple air conditioners, set schedules, monitor energy consumption, and receive real-time alerts.
Thanks to this complete ecosystem, Leaf AI is easy to deploy, easy to scale, and compatible with many popular air conditioner brands on the market.

2.3 Key Features of Leaf AI Technology in Energy Management
Leaf AI stands out thanks to technology advantages that traditional HVAC solutions cannot easily offer:
- AIoT Learning: The system keeps learning from real data (weather, humidity, occupancy) to adjust cooling/heating modes more effectively.
- Automation & Zone Optimization: Instead of controlling the whole building at once, it analyzes and adjusts precisely for each occupied zone, saving maximum energy.
- Multi-Brand Compatibility: Works well with major air conditioner brands such as LG, Samsung, Carrier… Businesses can apply it immediately without replacing current systems.
- Clear Emission & Cost Reduction: No trade – off with user comfort; Leaf AI maintains a pleasant temperature while cutting CO₂ emissions, supporting ESG and Net Zero goals.
- Comfort Assurance: No trade – off with user comfort, Leaf AI maintains a pleasant temperature while cutting CO₂ emissions, supporting ESG and Net Zero goals.

From temperature analysis to fault prediction, Leaf AI delivers superior energy efficiency and clear cost reduction.
2.4 Real-World Success Cases of Leaf AI
| 1. A Twosome Place (Franchise Café) |
– Saved up to 50% energy per month in summer. – Reduced average cost by 3 million KRW/month (~USD 2,300). – In 8 months, total savings reached about USD 13,000. |
| 2. H&M Retail | – Reduced total electricity use by an average of 16%, equal to more than USD 5,000 per year for one site. |
| 3. Hanssem Office | – Some sites cut 85% of air conditioning power when switching from normal mode to Leaf AI. |
| 4. Ediya Coffee & Lotteria | – This F&B chain saved about 20% of energy thanks to the smart energy management system. |
| 5. Starbucks | – Reduced energy use by 7 – 10% compared to the previous year, while sites without Leaf AI saw an increase of 5 – 20%. |

3. Potential for Cooperation and Commercialization of Leaf AI Technology
3.1 Huge Potential in the ASEAN Market:
The energy management market in Asia is growing strongly, with a CAGR of about 14.5% until 2033. In ASEAN, the demand to cut electricity costs and comply with ESG standards is becoming urgent, especially in energy – intensive sectors such as retail, F&B, offices, and factories.
Leaf AI directly meets this demand thanks to its flexible deployment: a web/app platform for centralized management combined with hardware connected directly to air conditioners, compatible with multiple brands. This solution can be easily scaled in cities, where operating costs are high and ESG pressure is rising.
3.2 Opportunities for Research and Development:
Investment in R&D for Leaf AI not only strengthens technical capacity but also creates attractive economic opportunities:
- Expanded Proof of Concept (POC): Results from H&M, Starbucks, Lotteria, and Hanssem show 10 – 50% energy savings. If deployed for 100 stores, businesses could save millions of USD annually while cutting thousands of tons of CO₂.
- Integration with Major AC Brands: With its complete system (Hub, Sensor, IR Controller) and compatibility with LG, Samsung, Carrier, Leaf AI can be pre-integrated into air conditioners, creating long – term revenue streams and promoting more energy – efficient devices.
- Standardization through ESCO Model: When Leaf AI becomes a standard smart energy management system for energy-saving services, businesses both reduce operating costs and meet emission requirements on the Net Zero 2050 roadmap.
- Expansion into Green Finance/Carbon Credit: Transparent emission reduction data allows businesses to join the carbon credit market, gain tax incentives, and access green investment funds.
These research directions not only create short-term economic value but also build the foundation for Leaf AI to become a strategic product in ASEAN’s journey to net zero emissions.

3.3 Strategic Value for B2B Partners
Leaf AI is not only about saving costs. It also creates long-term competitive advantages, helping B2B partners position themselves as leaders in smart energy management system adoption.
- Short-term: Businesses that deploy Leaf AI can immediately reduce HVAC electricity costs by 10 – 50%, saving tens of thousands of USD each year for retail chains, cafés, or offices
- Mid-term: With wider adoption, businesses can strengthen their image as a “green brand,” meet ESG reporting requirements, and attract both customers and investors who care about sustainability.
- Long-term: Large – scale deployment of Leaf AI helps build a huge HVAC data network in ASEAN. This becomes a strategic asset that can be used to develop more AI – driven services and participate more deeply in the global carbon trading market.
Leaf AI has clearly proven its effectiveness in helping businesses save 10 – 50% of HVAC electricity, reduce emissions, and improve ESG. It is not only a smart energy management system, but also an opportunity to grow into a sustainable commercial product in ASEAN.

If you are a business or organization interested in developing and commercializing Leaf AI, contact us today. Mekonglink is your strategic partner to connect research, pilot projects, and market entry in ASEAN.
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