Every agricultural answer traced back to the source
GroundTruth puts research-grade, land-grant-verified agricultural knowledge behind a simple API — so your product can answer growers' questions without guessing, and show exactly where each answer came from.
A confident wrong answer costs more than no answer.
General-purpose AI is fluent on agricultural topics and wrong often enough to matter — wrong on regional pest pressure, wrong on label restrictions, wrong on the difference between what works in Iowa and what works in Georgia. In production, "confident" and "correct" are not the same claim.
"Brown spots in your bermudagrass are usually fungal — try a broad-spectrum fungicide."
No source. No region. No way for the grower — or you — to check the claim before it's acted on in a field.
"In Oklahoma, this pattern matches Spring Dead Spot — confirm with a soil potassium test before treating.1"
Localized to the grower's state, grounded in a named Extension publication, and honest when the answer needs a soil test rather than a guess.
Three layers between your product and 50+ years of Extension research.
GroundTruth is built on the same aggregation infrastructure that powers ExtensionBot for the Cooperative Extension System — continuously refreshed, never a one-time export.
A living network of land-grant content
Fact sheets, publications, and advisory answers pulled continuously from land-grant Extension institutions across the country, plus vetted partners like the Crop Protection Network.
Grounded, not generated from memory
Every query is matched against verified source documents first. The model answers from what's retrieved — and says so plainly when nothing in the network answers the question.
Cited answers, your interface
Call the API directly and render answers, citations, and confidence in your own UI — or drop in the widget and go live in an afternoon.
Built for the parts of AI that make agronomists nervous.
Cited by default
Every answer carries source links a grower or advisor can open and check — not a bibliography bolted on after the fact.
State-aware localization
Weighted by region, so a question from Georgia and the same question from Minnesota get different, correct answers.
Model-agnostic
The underlying LLM can be upgraded or swapped without touching your integration — you're building on the retrieval layer, not one model's quirks.
Honest no-match handling
When the network doesn't have a confident answer, GroundTruth says so and routes to a local Extension office rather than filling the gap with a guess.
Continuously refreshed
Nightly incremental crawls mean new bulletins and updated guidance reach the API automatically, not on your next data refresh cycle.
API or widget
Full control via REST API for custom experiences, or an embeddable chat widget when you want something live fast.
Benchmarked and field-tested, under a different name.
GroundTruth runs on the same retrieval and citation infrastructure as ExtensionBot, the Extension Foundation's public agricultural chatbot — independently benchmarked against 26 other AI tools and field-tested by working Extension scientists. Here's what they found.
Bring verified agricultural intelligence into your product.
API access starts with a scoped pilot against your own use case — no long procurement cycle required.