AI solutions
for the infrastructure, energy industries
The infrastructure sector faces increasing disaster risk and the complexity of urban functions. We utilize satellite and time-series data analysis and simulation technology to support stable operation through wide-area monitoring and fault prediction, contributing to the construction of sustainable and resilient social infrastructure.
Use Cases
Energy Companies
Anomaly Detection and Predictive Maintenance at Power Plants
Electricity Demand Forecasting and Supply Optimization
Disaster Recovery Simulation
Telecommunication
Voice Deepfake Detection
Network Optimization through Data Analysis
Automated Customer Support
Urban Development & Transportation
Urban Monitoring with Satellite Imagery
Traffic Simulation for Congestion Reduction
Infrastructure Deterioration Detection and Prediction
How We Solve
Solutions
From video and speech to language and sensor data, our expert team builds AI solutions that tackle real-world challenges using deep learning.
How We Solve
FAQ
How long does it take to complete a PoC?
Although it depends on the task and the state of data preparation, in most cases results can be confirmed within 2 to 3 months. For small-scale testing, it is possible to complete it in about 1 month.
How should I estimate costs (initial costs and operating costs)?
Can AI prevent power outages and communication disruptions?
Yes. AI can learn from past failure logs and equipment data and detect signs of deterioration or abnormalities in real time. This enables predictive maintenance that takes measures before serious failures occur.
Is it possible to take measures to shift peak demand using energy demand forecasts?
Yes. By combining weather data and consumption patterns, we can predict sudden surges in demand and help spread out peak periods, which can help reduce power costs and the risk of power outages.