This company provides innovative smart heating control systems designed for existing building infrastructure. Their solution achieves significant energy savings, often up to 30%, without requiring major structural renovations. By improving energy efficiency, the service helps property owners reduce operational costs and meet sustainability targets.
Funding
Funding not disclosed
Founders
Product
Problem
Many existing heating installations in residential and commercial buildings operate inefficiently, leading to high energy bills and difficulty meeting climate‑reduction targets. Retrofitting these systems typically requires costly structural work and prolonged downtime, discouraging property owners from pursuing energy upgrades.
Solution
Cosy.green delivers an AI‑powered heating optimization platform that retrofits onto the building’s current boiler or district‑heating infrastructure without any civil works. Smart sensor modules collect temperature, flow, and weather data, which the cloud‑based algorithm uses to continuously adjust setpoints and pump speeds for optimal performance. The system can reduce heating energy consumption by up to 30% while maintaining indoor comfort, delivering a payback period of roughly 18 months. Energy savings are reported in real time through a web dashboard that also provides compliance documentation for EPC ratings and carbon‑reporting. Installation is completed in a few hours by a certified technician, after which the solution operates autonomously with remote monitoring and over‑the‑air updates.
Target Audience
The primary customers are owners and managers of multi‑family residential complexes, commercial real‑estate portfolios, and housing associations seeking to lower heating costs and improve energy‑efficiency certifications without major renovations.
Features
- Plug‑and‑play hardware kit that attaches to existing radiators, boilers, or heat‑pump controls without pipe modifications
- Edge AI engine that processes sensor streams locally and refines control strategies via cloud‑based machine‑learning models
- Real‑time analytics portal with energy‑use visualizations, ROI calculators, and automated EPC‑rating reports
- Seamless integration with common building‑management systems (BACnet, Modbus) through an open API
- Mobile app for property managers to view performance metrics, receive alerts, and schedule maintenance visits
- Secure, encrypted data transmission and storage meeting GDPR and industry‑specific compliance standards
- Automatic firmware updates and remote diagnostics to minimize on‑site service calls