What we built: From manual observation to intelligent precision

In agribusiness, every decision starts with one key question: how much will this field yield?

For one of the country’s largest agro-industrial companies, yield estimation still depended on field visits, manual sampling, and subjective interpretation.

With IAIAOH, we explored how a focused AI proof of concept could bring scientific precision to yield prediction, turning fragmented data into a consistent, decision-ready signal.

The challenge: Inconsistent estimates, slow processes, and zero traceability

Yield estimation relied heavily on human judgment and limited samples, creating uncertainty at scale. The main challenges were:

• Different agronomists = different estimation criteria

• Small, unrepresentative field samples

• Manual workflows slowing down decisions

• Lack of traceability and unified data

The core question: Could AI standardize yield estimation, improve accuracy, and accelerate decisions—without replacing agronomists’ expertise?

How we built it: Predictive intelligence that learns from the land

We built IAIAOH, a predictive AI proof of concept that combines multiple data sources to estimate soybean yields at the field level.

The solution integrates:

• Multispectral satellite imagery (NDVI, RedEdge)

• Climate signals such as temperature, rainfall, and soil moisture

• Machine learning models trained on historical harvest data

• A geospatial dashboard with early alerts and automated reports

• An API-ready architecture designed to integrate with existing enterprise systems

Instead of replacing agronomists, the model acts as a validation layer, reducing bias while strengthening expert decision-making.

Key accomplishments: What the POC proved

Even as a proof-of-concept stage, IAIAOH demonstrated strong potential impact:

• Up to 80% reduction in estimation errors

• 25% improvement in climate-related yield predictions

• 15–20% operational savings through fewer field visits and rework

• Faster, data-driven decisions with full traceability