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Agricultural Finance Intelligence

Ground-Truth WaterRisk Analytics

Proprietary sensor data for ag lending, farmland valuation, and crop insurance underwriting

Model Accuracy
Field-Tested
LOSO & Temporal validation
Ground Truth Data
9+ Years
34 sensor sites
Sensor Records
34+ Sites
9+ years of data

Target Markets

Institutional-grade water risk intelligence for agricultural finance

PRIMARY

Ag Lenders & Insurance

Risk assessment & underwriting
Enterprise
Contact for pricing
  • Water stress risk scores per parcel
  • Portfolio-level exposure analytics
  • Loss ratio prediction models
  • SGMA compliance monitoring
EXAMPLE CLIENTS
Rabo AgriFinance, Farm Credit, crop insurers

Farmland REITs

Asset valuation & due diligence
Per Engagement
Contact for pricing
  • Water availability assessments
  • ESG reporting data
  • Acquisition due diligence reports
  • Long-term sustainability scores
EXAMPLE CLIENTS
Gladstone Land, Farmland Partners, ESG funds

GSAs & Water Districts

SGMA compliance & planning
Enterprise
Contact for pricing
  • Basin-wide usage analytics
  • SGMA reporting automation
  • Allocation optimization models
  • Groundwater sustainability plans
EXAMPLE CLIENTS
Kern Groundwater Authority, water districts

The Data Advantage

First-mover advantage in agricultural water intelligence

9+

Years of Sensor Data

Multi-depth soil moisture readings from 34 sensor sites across the Central Valley

34+

Active Farm Sites

Proprietary T6 irrigation event data - the only dataset linking conditions to farmer decisions to outcomes

40+

Years Expertise

Multi-generational agronomic knowledge from Certified Crop Advisors embedded in our models

Use Cases

How agricultural finance professionals use ORACLE data

Loan Underwriting
Crop Insurance Pricing
Farmland Acquisition
ESG Reporting
SGMA Allocation
Portfolio Risk
Water Rights Valuation
Due Diligence

Data Ethics & Privacy

Our commitment to responsible data usage

ORACLE uses only aggregated, anonymized basin-wide data

No individual farm identification possible in our intelligence feeds

Compliant with GDPR, CCPA, and agricultural data privacy standards

The Data Moat

Why this dataset is irreplaceable

  • 9+ Years of Ground Truth Data

    6.4 million sensor readings from 34 sites with validated stem water potential (SWP) measurements. Took 9+ years to build - cannot be replicated.

  • Proprietary T6 Pump Data

    3.8 million irrigation event records showing exact pump on/off times. Only dataset linking conditions to actual farmer decisions to outcomes.

  • Multi-Depth Root Zone Analysis

    Multi-depth soil moisture profiles at each site. Competitors only have satellite imagery - we have real ground truth across the full root zone.

  • 16 Years of Irrigation Expertise

    Data validated by Certified Crop Advisors with 16 years of irrigation expertise. Every reading contextualized with expert knowledge.

Request Data Sample & Methodology

Get sample data and our methodology brief to evaluate fit for your models.

EVALUATION INCLUDES
Sample CSV + Methodology Brief + 30-min Walkthrough

Important Disclosures

Not Investment Advice: The data and information provided by AgWaterAI ("Data") is for informational purposes only and does not constitute investment advice, financial advice, trading advice, or any other sort of advice. AgWaterAI is not a registered investment adviser, broker-dealer, or commodity trading advisor. You should not treat any of the Data as a recommendation to make any investment decision.

No Warranty: The Data is provided on an "AS IS" and "AS AVAILABLE" basis. AgWaterAI expressly disclaims all warranties of any kind, whether express or implied, including warranties of merchantability, fitness for a particular purpose, accuracy, and non-infringement.

Limitation of Liability: In no event shall AgWaterAI be liable for any lost profits, trading losses, or any indirect, consequential, special, punitive, or incidental damages arising from your use of the Data, even if advised of the possibility of such damages.

Data Sources: Data is derived from proprietary sensor networks with farmer consent. All data is aggregated and anonymized. Individual farms cannot be identified.