Advancing climate-informed crop forecasting research

Where the world's
crops should grow next.

A research-driven platform combining crop models, climate models, and geospatial AI for yield forecasting of major strategic crops — season by season, over the next 15 years.

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croptimize.tech / dashboard / wheat — north america
Suitability score
0.0
+4.2 vs last cycle
Risk index
Low
2030 horizon
Yield projection
+0%
vs current sourcing
Explore what the platform can model for your region.
15-minute research briefing · region and crop specific.
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— Regional forecasting

Regional crop forecasting powered by climate models, crop models, and geospatial AI.

Drag to explore. Each marker represents a region where our climate-crop models have been applied or validated.

Optimal
Caution
Declining
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— The problem

Strategic crop planning has not kept pace with climate change.

Sourcing decisions for major strategic crops are still largely based on historical yield data and static geographic assumptions. As climate conditions shift, these baselines become increasingly unreliable for long-term planning.

$0B
Projected food-production losses by 2030
0%
Forecast increase in crop failure events
0×
California-equivalents of farmland at risk
— How it works

From data integration to actionable forecasts.

01

Ingest

We integrate remote sensing data, soil profiles, meteorological records, and crop physiology inputs for selected strategic crop regions.

02

Model

Integrating numerical crop models, regional climate models, and machine learning algorithms to forecast yields of major strategic crops, season by season, over a 15-year horizon.

03

Decide

Research outputs are translated into region-level suitability assessments, risk indicators, and scenario-based planning tools for institutional and commercial decision-makers.

— Traction

Argentina pilot — proven results.

Applied pilot in Entre Ríos, Argentina, with design partner Luis Urriza. Approximately 1.37 million hectares analyzed using integrated climate-crop modeling, with results validated against observed data.

Maize
+608,000 t
potential increase
+184%
Soybean
+152,000 t
potential increase
+96%
Wheat — Short Cycle
+237,000 t
potential increase
+78%
Wheat — Long Cycle
+175,000 t
potential increase
+64%
✓80%+ model accuracy validated against observed data in pilot regions
✓Climate risk became measurable and actionable
✓Forward-looking climate modeling outperforms static historical baselines
✓Pilot results support application as a strategic planning tool for food producers
— Science & research

Built on peer-reviewed science.

Our scientific foundation includes published and peer-reviewed research from Dr. David Helman's M&M-VS Lab at the Hebrew University of Jerusalem. Additional studies are currently under peer review.

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— The platform

Four integrated research capabilities.

Climate impact prediction

Regional climate projections integrated with crop-specific phenological models, calibrated for seasonal forecasting across a 15-year horizon.

Supply-chain risk assessment

Region-level risk indicators derived from climate model outputs and crop sensitivity analysis — supporting scenario-based supply planning.

Long-term cultivation planning

Geospatial analysis to identify and monitor suitable cultivation zones for strategic crops under projected climate scenarios.

Resource allocation

Scenario-based allocation modeling to support irrigation strategy, geographic prioritization, and production planning decisions.

Supporting institutions working across the food and agriculture system
Food manufacturers· Reinsurance· Trade finance· Commodity traders· Agri-funds
— Team

The science behind the platform.

A multidisciplinary team combining expertise in agronomy, climate science, geospatial research, finance, and technology — anchored by active academic research at the Hebrew University of Jerusalem.

Shai Gilboa
Shai Gilboa
CEO · 6 startups, 2 exits · Technion
Pamela Jramoy
Pamela Jramoy
CBO · ex-CABEI · $470M agri infra
David Helman
David Helman, PhD
CSO · Head of M&M-VS Lab, HUJI
Yaron Michael
Yaron Michael, PhD
Geospatial Director · remote sensing
Jonathan Ari
Jonathan Ari
CTO · ex-CLEER, MUV, Moblin
Gal Yarden
Gal Yarden, PhD
Board · ex-Monsanto, Bayer
Teddy Cohen
Teddy Cohen
VP Services, CFO, Co-Founder · CPA · 25yr IT & finance
— Questions

Frequently asked.

How is Croptimize different from existing climate risk tools?+
Most planning tools rely on historical baselines. Croptimize integrates forward-looking climate projections with crop modeling to support more robust long-term sourcing and production decisions.
Which crops do you currently model?+
Our current research focus covers major strategic crops including wheat, maize, and soybean, with ongoing model development for additional crops. Custom modeling scopes are available for institutional partners.
What's the data foundation behind the model?+
Our models fuse satellite remote sensing, soil composition data, multi-decade weather records and crop physiology — calibrated by Dr. David Helman's M&M-VS lab at the Hebrew University.
Is this for buyers, traders, or producers?+
All three. CPGs use it for sourcing strategy, traders for market positioning, insurers and lenders for risk pricing, and ag operations for cultivation planning.
How long does deployment take?+
Initial regional assessments are typically delivered within a few weeks. Implementation timelines vary based on scope and institutional requirements.

Plan for the climate that's coming.

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