Kestrix uses non-invasive machine learning and computer vision to map and quantify building heat loss at city scale. This technology enables energy retrofit planning by validating existing EPC data and rapidly prioritizing which homes require immediate attention. The platform also helps accurately price necessary retrofit interventions and verify decarbonization progress for stakeholders.
Funding
$3.2M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
MSFounders
Product
Problem
Many homes in Europe require energy retrofitting to meet CO2 emission reduction goals, but current methods for assessing heat loss are either inaccurate or too expensive and time-consuming for large-scale analysis. Existing Energy Performance Certificates (EPCs) can overstate energy use, and on-site surveys are costly and slow, hindering effective retrofit planning and prioritization.
Solution
Kestrix provides a solution for city-scale energy retrofit planning by using thermal drones and AI-driven computer vision to map and quantify heat loss from buildings. The technology rapidly identifies and ranks homes based on their energy performance, blending heat loss insights with geometric data to ascertain the best retrofit interventions for each home. This approach enables stakeholders to prioritize buildings needing attention, understand the costs of interventions, and validate the impact of retrofitting efforts before and after implementation. By providing accurate and scalable data, Kestrix facilitates de-risked retrofit strategies and helps measure progress toward net-zero goals.
Target Audience
Kestrix targets energy companies, local governments, and organizations involved in urban planning and energy retrofitting initiatives.
Features
- Thermal drone-based data acquisition for non-invasive heat loss mapping
- AI-powered computer vision for automated building analysis and quantification of heat loss (kWh/m2/yr)
- Rapid Thermal Performance algorithms (RaThPAs) for estimating energy performance
- Integration of heat loss data with geometric data to determine optimal retrofit interventions
- Prioritization of buildings based on energy performance for targeted retrofit efforts
- Validation of retrofit effectiveness through before-and-after thermal scans