TECHNOLOGY
An intelligent agent for smarter building energy operations.
CyanSE connects building data, engineering knowledge and AI control into a building intelligence agent. The agent understands equipment behaviour, predicts operational needs, recommends safe control actions, and helps buildings reduce energy use while maintaining comfort and reliability.
Building intelligence across data, AI control and digital twin interfaces.
Building Intelligence Agent
Turns building data, operating rules and engineering know-how into practical decisions for daily operation.
AI Optimal Control
Predicts demand and optimizes HVAC equipment such as chillers, pumps, AHUs, FCUs and air purifiers.
Scalable Deployment
Uses semantic data fusion to connect existing BMS, IoT and equipment data through a standardized data layer, reducing integration effort and enabling fast, repeatable deployment across different building types.
Digital Twin and Mixed Reality
Provides real-time visualization through web, desktop, mobile and Mixed Reality interfaces, helping teams see equipment status, indoor conditions and AI control actions more intuitively.
Learn together · Optimize together
Intelligence working together for better building operation.
Connected capabilities share a digital twin, engineering knowledge and live feedback to jointly optimize energy, comfort and operational safety.
Perceive · Shared operational context
Connect existing building systems, sensors, documents and operator input. Bring equipment, zones, weather and occupancy into a common view of real operation.
Reason · Domain-aware intelligence
Combine large language models, domain-specific AI and engineering knowledge with a semantic digital twin. Evaluate control options against equipment limits and operating requirements.
Act · Coordinated, safe control
Coordinate HVAC and energy systems around shared objectives. Deliver control recommendations or automated actions, with operator oversight through web, desktop and MR interfaces.
Learn · Continuous improvement
Feed measured performance and operator feedback into the shared models. Adapt decisions to changing demand and conditions, keeping all capabilities connected.