Verdex, a San Francisco–based artificial intelligence startup building satellite-powered insurance verification infrastructure, has raised early-stage venture funding as it scales its platform for automating crop insurance inspections and expanding its data-driven risk assessment systems across the agricultural sector.

The company, founded in 2025 by Evan Rankin and Jad Bousselham, develops an AI-enabled digital audit system that replaces traditional on-the-ground insurance inspections with real-time satellite imagery analysis. Its platform is designed to help insurers verify agricultural claims, monitor field conditions, and settle payouts without requiring physical field adjusters, significantly reducing operational costs and claim processing times.

Verdex has raised approximately $500,000 in pre-seed funding, according to startup financing data, with backing tied primarily to its participation in Y Combinator’s Winter 2026 cohort. The accelerator serves as the company’s primary institutional investor, providing early capital along with structured mentorship, product development support, and access to a global network of enterprise and insurance industry partners.

The involvement of Y Combinator reflects growing investor interest in geospatial AI infrastructure, particularly applications that combine satellite imagery, weather modeling, and machine learning to modernize legacy insurance workflows. Verdex’s inclusion in YC’s program has also helped the company gain early traction with large agricultural insurers in the United States.

The startup is currently live with a major U.S. crop insurance provider, where its system is used to monitor more than 100 million acres of farmland—representing over 11% of total U.S. agricultural land. This deployment marks a key validation milestone for the company’s technology, demonstrating real-world usage of satellite-based claim verification at scale.

Verdex’s platform integrates high-resolution satellite imagery with weather and environmental data to create a persistent, time-stamped record of agricultural conditions. This enables insurers to detect anomalies, verify damage claims, and assess risk exposure with significantly higher speed and consistency compared to traditional field inspection models.

The company’s AI systems are trained to identify crop health indicators, detect temporal changes in field conditions, and evaluate potential fraud or misreporting in insurance claims. These capabilities are particularly relevant in an environment where climate volatility has increased both the frequency and complexity of agricultural insurance claims.

In addition to its crop insurance focus, Verdex has outlined plans to expand into adjacent insurance verticals such as property and energy insurance. This expansion strategy is based on applying the same satellite-to-claim verification pipeline to other asset classes that can be monitored remotely through geospatial data.

Industry investors see Verdex as part of a broader shift toward automation in insurance operations, where manual inspections are being replaced by AI-driven remote sensing systems. The company’s approach aims to reduce reliance on field adjusters, accelerate claims resolution, and improve underwriting accuracy through continuous monitoring rather than episodic inspections.

The $500,000 in early-stage funding is being used to expand engineering capacity, refine its machine learning models, and scale deployments with additional insurance partners. Verdex is also investing in improving its geospatial analytics pipeline, which combines satellite imagery, environmental data, and predictive modeling to generate actionable insights for insurers.

With backing from Y Combinator and early deployment across millions of acres of farmland, Verdex is positioning itself as a foundational infrastructure provider for the future of insurance verification, where satellite data and AI replace traditional field-based assessment workflows in agriculture and beyond.

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