ResiQuant provides an AI platform for natural catastrophe property insurance underwriting, integrating automated workflows with engineering-grade intelligence. The platform utilizes modular AI agents to handle submission processing, structural validation, and guideline enforcement for perils like earthquake, wildfire, and windstorm. This solution enables property carriers and MGAs to significantly reduce manual workload and increase underwriter capacity across complex US property markets.
Funding
$4.7M 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
Insurance carriers face challenges in efficiently processing property submissions and accurately assessing risk due to reliance on manual data entry, unstructured documents, and outdated building characteristics. This can lead to errors in underwriting, incomplete portfolio insights, and ultimately, reduced profitability.
Solution
ResiQuant offers an AI-powered platform that automates the ingestion and processing of property submissions, extracting key data points from various document types, including handwritten ones. The platform enriches this data with up-to-date building characteristics, incorporating structural engineering expertise and knowledge of evolving building codes and ordinances. By providing a single source of truth for property data, ResiQuant enables insurance carriers to gain comprehensive portfolio-level insights, improve underwriting accuracy, and enhance long-term profitability. The system converts building characteristics to RMS and Verisk model inputs.
Target Audience
The primary target audience is insurance carriers seeking to automate property submission processing, improve underwriting accuracy, and gain deeper insights into their book of business.
Features
- Automated submission intake using advanced computer vision to process unstructured documents.
- Multi-file upload supporting various file types with drag-and-drop functionality.
- Submission scoring to vet data quality and coverage.
- Data enrichment with up-to-date building characteristics, including primary and secondary modifiers.
- AI models trained on structural engineering inspection procedures.
- Dynamic data source reflecting new retrofits, permits, and local ordinance changes.
- Portfolio-level insights and regulatory updates in real-time.
- Conversion of building characteristics to RMS and Verisk model inputs.