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AGMRI AI Agent

What is it?

The AI Agent is a conversational agronomic assistant that helps advisors and growers analyze field data and generate insights in real time. Instead of navigating multiple dashboards, users can ask questions in natural language—or collaborate with the system on an analysis—and receive field-specific insights based on connected agronomic data such as:

  • Crop plans
  • Soil data
  • Imagery
  • Product applications
  • Historical field performance

Where do I find it?

↑ On the web: Access the AI Chat in the upper left corner of the dashboard.

→ In the app: Navigate to more and choose AI Chat.

Start your conversation!

Questions to Ask

The AI is built to answer real agronomic and business questions, such as:

  • Should fungicide be applied in this field?
  • Which hybrids perform best on different soil types?
  • Where are the biggest yield gaps across this operation?
  • What is the expected ROI of a product application?
  • What changed in underperforming fields year-over-year?

Here are some example starter prompts:

  • Grower Performance Overview: “Give me a performance overview for [GROWER NAME] in [YEAR]. Include yield summary, field count, crop mix, and top and bottom fields.”
  • Hybrid Performance Comparison: “Compare hybrid performance for [GROWER NAME] in [YEAR]. I want to see yield by soil productivity tier. Focus on [corn/soybeans]. The hybrids I care about most are [HYBRID 1, HYBRID 2, HYBRID 3].”
  • Weather Planning: “What’s the weather forecast for [COUNTY, STATE] this week? I’m planning [planting/ spraying/harvest] and need to know about [rain/wind/temperature].”

What it Can Access

  • Yield Data
  • Hybrid Info
  • Weather
  • Plant Performance
  • Soil Tests
  • Products
  • Imagery

What it Can Build for You

  • Charts & Tables
  • Shareable reports
  • Prescription (.shp)*
  • Zone & Heat Maps
  • ROI Calculators
  • Field Map Links

* Prescriptions

AI Agent includes the ability to generate shapefile-based recommendations. Shapefile outputs should be considered a beta feature; we cannot guarantee the accuracy of shapefile recommendation. We strongly advise human verification before execution.

LLM Components

7 Key Components of an LLM System

A plain-language chart explaining the major components of an LLM system using practical farm and agronomy analogies.

1

Custom Agent

Description: Who’s talking to you

Details: Standard gives you a general-purpose analyst. Custom means your co-op or retailer has its own version tuned to how your team works.

Example: Like texting your local agronomist who’s walked your fields for 10 years, instead of calling an 800 number.

2

Data

Description: What they know about your farm

Details: All the information about your fields, such as yield maps, planting history, soil types, weather, inputs, and harvest data. Custom adds your own proprietary layers.

Example: The county plat book plus your grandpa’s drainage tile maps and 20 years of yield books.

3

Memory

Description: What they remember from last time

Details: The system remembers your preferences, what you worked on, and what’s still on the to-do list so you never have to re-explain your operation.

Example: “Remember that wet spot on the south 80 we talked about in November?” — and it does.

4

Analysis

Description: How they think through problems

Details: Compares hybrids, checks if yield differences are real or just better dirt, and screens out bad data. Thinks like a good agronomist, not a calculator.

Example: “Did that hybrid actually do better?” It checks soil, rain, and population before answering.

5

Skills

Description: Ready-made reports they can run

Details: Pre-built analyses that run with one click, generating hybrid report cards, field comparisons, yield gap breakdowns. Custom skills match how your retailer does business.

Example: Standard plays every team runs, plus the trick plays your coach drew up for your team.

6

Artifacts

Description: The finished product you can hold

Details: Charts, dashboards, maps, and tables you look at. Share with your landlord or hand to your agronomist at the kitchen table.

Example: A clean, color-coded map of your farm you’d tape to the shop wall or email to your cash rent landlord.

7

Knowledge

Description: The textbook they can look things up in

Details: Reference material the system can pull from: growing degree day requirements, soil test interpretations, disease pressure thresholds, seed trait matrices, and Extension research. Your agronomist doesn’t just know your farm—they know the science behind the answer.

Example: A sharp agronomist with the Purdue Extension bulletins, the seed trait matrix, and 30 years of plot data sitting right next to him.

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Yield Forecast

Understand where your corn yield is based on the current state of the crop. As the season unfolds, see how it is having an impact on your final yield.

Yield Loss

Powered by years of Nitrogen research at the University of Missouri, our corn Yield Loss analytic, powered by NVision Ag, gives insight into potential yield loss due to Nitrogen deficiency. Optional analytic for nitrogen management.

Variable Dry Down

variable dry down

Understand which fields and which areas of the field are drying down to help plan your harvest logistics.

Underperforming Area

low crop health

Not all areas of your fields perform the same and low NDVI doesn’t necessarily mean there is anything you can do to fix it this year. Underperforming Area alerts you to the fields and areas of the fields that are performing below their historical potential. This will allow you to quickly find those fields and areas and make adjustments to get them back on target and protect yield.

Nutrient Deficiency

nutrient deficiency

As the crop grows, it can tell us more of what is wrong with it. This analytic finds the fields and areas of the fields where there is a nutrient deficiency so that issues can be addressed before grain fill.

Disease Stress

disease risk

In conjunction with the Thermal Stress, Disease Stress alert takes into account weather information to more precisely indicate the type of stress impacting the crop.

Thermal Stress

thermal risk

Using our thermal imagery, AGMRI can detect elevated heat patterns of the crop that indicate crop stress.

Crop Health

Crop Health

Get a complete view of your farms and fields and identify where yield potential is ranked highest to the lowest.

Weed Map & Weed Escape

weed escape

Know what fields and areas of the fields have weeds. With machine integration or based on planting date, be alerted to what fields have weeds that may be impacting yield.

Historical Field Performance

AGMRI creates 5 performance zones in each field based on the historical average of those zones. This data is used to compare the current season to help understand where you are underperforming from the zone potential.

Low Emergence

low emergence

Notification of what fields and areas of the field have poor emergence.

Stand Assessment

strand assessment

AGMRI detects the established rows and uses computer vision and machine learning to determine the best segment of row and compares the rest of the field to that segment to give you a relative map. If machine data is integrated, a stand population map is returned.

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