Spotr utilizes AI-driven image analysis to conduct remote inspections of buildings, enabling the rapid assessment of property conditions and compliance with regulations. This technology addresses the issue of underinsurance by providing accurate data on property conditions, helping insurers and housing associations optimize risk management and operational efficiency.
Funding
$9.3M 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.
Founders
Product
Problem
A significant portion of properties are underinsured due to inaccurate or outdated assessments of building conditions, leading to financial risks for both insurers and property owners. Traditional property inspections are costly, time-consuming, and difficult to scale across large portfolios. This creates challenges for insurers, housing associations, and banks in managing risk, optimizing operational expenses, and complying with regulations.
Solution
Spotr offers an AI-powered remote inspection platform that enables rapid and scalable assessment of property conditions using image analysis. The platform creates a visual twin of each property, incorporating roof, façade, context, and interior images. Computer vision algorithms analyze these images to detect building condition, elements, typology, materialization, and derive measurements. This allows insurers to proactively prevent underinsurance, housing associations to optimize operational expenses, and banks to identify changes in energy labels to improve Loan to Value Ratios. The platform delivers data and insights through a visual platform or API, enabling users to prioritize properties based on specific risks or opportunities.
Target Audience
Spotr primarily serves insurers seeking to protect customers against underinsurance, housing associations aiming to optimize operational expenses, and banks looking to improve Loan to Value Ratios.
Features
- AI-driven image analysis to detect building condition, elements, typology, and materialization
- Creation of a complete visual twin of properties, including roof, façade, context, and interior images
- Automated scoring system to highlight properties needing attention
- API integration for seamless data export into existing systems
- Generation of property reports including flora & fauna quickscans, NEN2767 condition assessments, rebuild valuations, fire risk scans, and housing health & safety checks
- Identification of risks associated with properties
- Detection of outdated energy labels