Problem/Solution Report

Problem

Crop insurers historically rely on manual, on‑the‑farm field inspections to verify losses, assess replant practicability, and document conditions. USDA’s Loss Adjustment Manual mandates numerous cases requiring field inspections and detailed documentation. Pain points include extensive travel mileage, limited visibility (inspectors see only a fraction of fields), slow claim cycles, and portfolio‑level blind spots during catastrophes (flood, drought, hail). Verdex asserts adjusters drive hundreds of millions of miles annually and that manual inspections incur multi‑billion‑dollar costs.

Solution

Verdex provides asset intelligence for farmland using satellite imagery and weather data to create a persistent, time‑anchored record for every acre. This enables objective, auditable verification at scale, replacing many manual field inspections and allowing adjusters to focus on complex claims. The platform continuously monitors fields, tracks disasters in real time, and compiles longitudinal field histories to inform underwriting, risk management, and claims decisions – “see the whole field, all the time.”

Value Proposition

• Faster, lower‑cost claim verification with fewer truck‑rolls.
• Improved accuracy and auditability through longitudinal satellite‑derived evidence.
• Portfolio‑level visibility to triage and manage catastrophic events in real time.
• Potential to reduce administrative/operating and loss‑adjustment expenses while increasing insurer capacity during peak events.

Verdix’s messaging (YC and company materials) emphasizes replacing manual inspections in insurance verification and risk management, rather than broader farm‑management use cases.

Market and Competitors Report

Market Overview

Verdex operates at the intersection of agricultural insurance, remote sensing, and risk analytics. The Federal Crop Insurance Program and private crop‑insurance ecosystem cover hundreds of millions of acres and near‑$200 billion insured value (2024). Program‑delivery costs (A&O subsidies) are substantial, creating a sizable opportunity for remote‑sensing verification to reduce spend.

Key Competitors

• EOS Data Analytics (EOSDA) – Satellite‑based crop monitoring for insurers, offering tools for hail, drought, flood detection and index/parametric designs.
• Athenium Analytics – Provides weather and severe‑event forensic datasets (e.g., Dexter) to help claims teams verify post‑event weather quickly.
• SatSure – EO‑powered solutions for insurance and reinsurance, including crop health tracking, rapid claim settlement and climate‑risk alerts.
• EarthDaily Agro / Geosys – Established ag‑remote‑sensing platform used by insurers and reinsurers for risk and claims workflows.

Differentiation

Verdex focuses explicitly on insurance verification with a persistent, per‑acre record designed to replace manual field inspections. Its messaging emphasizes auditable outcomes at scale for insurance and risk management, rather than broader agronomy or farm‑management services.

Go‑to‑Market Considerations

Strategic alignment with approved insurance providers, reinsurers and adjuster networks; integration with claim systems; validation against USDA/RMA documentation standards; targeting specialty‑crop segments where A&O caps are acute; and expanding to parametric or hybrid verification schemes as climate volatility drives demand.

Overall, the market is sizable and growing, with several established remote‑sensing players. Verdex’s niche focus on inspection replacement gives it a clear competitive advantage in the insurance verification niche.

Founders’ Background Report

Verdex was founded by Jad Bousselham and Evan Rankin. Both are recent Dartmouth affiliates, bringing technical depth in applied machine learning, geospatial data, and engineering.

• Jad Bousselham holds a master’s degree from Dartmouth’s Guarini School with research focused on agricultural remote sensing and machine learning. His 2025 master’s thesis, High‑Accuracy Soybean Yield Prediction Using Multispectral Satellite Data, demonstrates direct experience building geospatial ML models for crop outcomes. He has also published research on protein‑structure LLMs, indicating broad AI competency.
• Evan Rankin is a Dartmouth ’25 from Maine and a recipient of the Dartmouth Society of Engineers Prize for outstanding engineering projects. Prior press highlights a robotics and STEM background that fed into his engineering studies at Dartmouth.

The company is backed by Y Combinator (Winter 2026). YC lists both founders and describes Verdex’s mission and technical focus. Verdex’s own site also notes “Backed by Combinator.”

Together, the founders combine (a) geospatial/remote‑sensing ML for yield prediction and agricultural analytics, (b) practical engineering execution and product building, and (c) early validation and traction through YC and Dartmouth‑affiliated innovation programs.