This SaaS platform helps crop insurers reduce costs by using remote sensing data to monitor fields and verify claims. By providing accurate, real-time insights into crop health and yield, the platform enables insurers to improve pricing and reduce the need for in-person inspections.
Funding
Funding not disclosed
Founders
Product
Problem
Crop insurers face challenges in accurately monitoring fields and verifying claims, leading to increased costs and potential fraud. Traditional methods often rely on manual inspections, which are time-consuming, expensive, and may not provide a comprehensive view of crop health and yield. This lack of real-time, accurate data hinders effective pricing and risk management.
Solution
GreenTriangle offers a SaaS platform that leverages remote sensing data and AI models to provide crop insurers with reliable crop monitoring and claims management. The platform combines ground sampling data with regional and local remote sensing to deliver field-level insights. By integrating a web app, mobile app, and API, GreenTriangle enables users to automate loss adjustment processes, forecast yield, and price new insurance products. The system facilitates seamless communication between insurers, loss adjusters, and farmers, ensuring cost-efficient and reliable claims reporting.
Target Audience
The primary target audience includes agriculture insurers, reinsurers, loss adjusters, farmers, and food processors seeking to reduce costs, improve accuracy, and manage risk in crop monitoring and claims management.
Features
- Digital Claims Management tools for automated and seamless claims processing
- Yield Forecasting models combining ground sampling and satellite data with AI
- Hybrid parametric indexing for pricing insurance products and adjusting claims
- Mobile app for systematic field data collection and real-time data access
- Web app for portfolio management and performance monitoring
- API for integration with existing systems
- Remote sensing maps on mobile and web app, including satellite imagery, intra-field variability, and soil moisture anomaly
- Tools to manage moral hazard and fraud
- Support for various grain types with week-by-week regional and field-level yield forecasts