FBN and Google Build AI “Context Engine” for Farms

Starting this fall, FBN’s Norm will surface daily, farm-specific insights, and by spring it aims to act on them, with Google supplying the AI models.

FBN logo.png
FBN logo.png
(FBN logo)

Farmers don’t lack data. They lack the time to connect it. A yield forecast sits in one system, grain bids in another, input prices in a third, and the weather changes all of them. Farmers Business Network (FBN) and the Google AI Futures Fund announced a partnership this week to close that gap with what they call agriculture’s first AI Context Engine.

FBN has spent a decade building the pieces, which the Context Engine is now meant to realize as an integrated, 360-degree picture of each farm, covering soils, crops, equipment and finances, and layered with local weather and market conditions.

“AI takes problems that once took weeks or months, or were expensive to evaluate, and gives farmers a holistic view instantly, in real time,” says Charles Barron, FBN’s co-founder and chief marketing officer.

Google will give FBN early access to frontier models and model-development expertise. FBN will test those models against complex agricultural reasoning tasks. Barron said Google has been a partner and investor since the company’s early days. The new work is with specific technical teams at Google, including the futures fund and DeepMind.

Connecting the dots

FBN’s Acre Vision tool has analyzed 15 million parcels of land. Its grain marketing platform, Gradable, offers 15-minute pricing at about 6,000 grain-buying locations. Seed Finder holds performance data on 6,000 hybrids.
The idea is to let those systems talk to each other. Barron says a grower could take an FBN yield prediction and have it translate directly into marketing and hedging strategies. Someone evaluating a parcel could weigh it against the seed, tillage and fertility practices that would be used on it.

What Norm has taught FBN

FBN launched the Norm AI Ag Advisor in 2023 as a chat-based agent, and Barron describes it as the AI backbone of the platform. It now serves the network’s 140,000-plus members, fielding questions on everything from crop protection to seed selection to equipment maintenance.

What FBN has learned, Barron says, is how varied those questions are. Farmers aren’t just asking for a product recommendation. One cotton, soybean and rice grower in Arkansas asked Norm for a five-year crop rotation based on inputs, cost of production and markets. “That’s what a producer is trying to solve,” Barron says, describing the “enormously complex problems” growers bring to the tool.

Watching how farmers frame those problems also showed FBN how broad the need is. Barron says the range of questions is broader and more flexible than any single software product could handle, and that answering them well takes structured data behind the AI. That is the reasoning behind the Context Engine. Norm is the layer meant to connect FBN’s separate tools, from yield predictions to grain pricing to product availability, so one question can draw on all of them.

The next step is for Norm to act on the answers as well as give them. Barron said farmers will be able to interact with Norm by voice, ask for advice, and then ask it to take an action, with the result “executed and analyzed via AI.”

The data question

Any partnership with Google will raise questions about farm data. Barron addresses that directly.
“Google is a technical partner on the models. Farmers’ data stays within FBN,” he says. “Data lives in FBN. That trusted relationship doesn’t change.” FBN is giving Google feedback on how the models perform on geospatial and weather tasks in agricultural settings.

FBN membership is free, and commerce, finance and grain marketing don’t require farmers to share data. The data-driven tools do, including benchmarking, yield predictions and Seed Finder, and the AI layers on top of those.
What’s coming, and when

Barron lays out a timeline in stages:

  • This fall: Farmers get “hyper-personal” insights, surfaced by the AI and delivered daily. Early product experiences are expected by the end of harvest.
  • By spring: The AI moves from advising to acting. Barron said it will help execute commercial actions such as buying products, getting payments and qualifying for sustainability programs.
  • In 12 to 24 months: A farm’s complete system could be integrated, with AI running on top of it.

The goal, Barron says, is for farmers to manage their operations on an integrated basis, with visibility into how each component affects the others. Those insights would adjust to weather and market conditions as they change.

“AI doesn’t replace how the crop is planted. The work has to be done,” he says. The changes will reach further, he added: seeds will be developed differently, as will crop protection products, sensors and imagery integration.
“This is just the beginning,” Barron says, calling the partnership flexible and noting that FBN is running multiple systems as it develops the platform. Farmers will soon see how much of that vision reaches their screens.

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