Using AI to Predict Crop Prices

At Xyonix, we regularly build AI and machine learning models to make predictions based on structured and unstructured data. Do you have an interest in accurately predicting crop prices from your data?

Predicting the price a given crop will yield in the future is extremely valuable when determining which types of crops to plant. Many variables go into predicting future prices for a given crop including but not limited to: climate, historical pricing, location, demand indicators, oil prices, and crop health. These and other related potentially predictive variables can be gleaned from myriad data sources including aerial imagery, weather, census, land use, market price and other data including your own.

We have extensive experience building predictive models on a variety of different types of data. Read about some of our recent projects below to get a taste of our capabilities.

projects
Manufacturing Engagement Optimizer

Manufacturing Engagement Optimizer

We worked closely with a large industrial parts marketplace provider to help them better understand their current customers and partners. We developed AI models trained on their customer and partner site usage, profile and external attribute data to analyze engagement. We were able to successfully forecast which customers and partners were destined for high and low engagement. Perhaps more importantly, our models were able to explain why customers were likely to be high or low engagers. These deep, data driven insights, when used to power a living intelligence dashboard, are able to direct sales and marketing activities so they are more efficient and impactful.

Customer Behavior Analyzer

Customer Behavior Analyzer

We worked very closely with executives of a major dental insurance company to help better understand their customers. We used historic data to predict future customer behavior and purchase selections. Our models predict which customers are likely to lapse, and which are likely to remain loyal. Our models are also explainable, so it is easier to understand which attributes of a customer are indicative of loyalty or lapse tendencies. In addition to understanding high level customer characterizations, our explainable models describe why a specific customer is predicted to be a lapser or loyalist.

 
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Dominique Grinnell
Dominique Grinnell

“I don’t think a five out of five really encapsulates the work that they do. The work is top-notch. It’s what we ask for and more. They go the extra mile in terms of letting us know that whatever we need, they’re there for us to lend their expertise, to be in a meeting if they need to, to explain the project in more detail. So it’s really going above and beyond.”

Dominique Grinnell, Sr. Product Team Manager at Delta Dental of Washington [more]

Want to dig deeper? Read more about how AI is transforming agriculture below.

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Farming is Dying – Can AI and AgTech Save It?
Farming is Dying – Can AI and AgTech Save It?

The global food supply is on the brink of crisis. Facing challenges like an aging workforce, labor shortages, declining crop yields, and climate change amongst others, farming is in dire need of a lifeline. AI and AgTech are emerging as the saviors of agriculture, transforming everything from crop breeding to farm-to-table traceability. These revolutionary technologies promise to enhance sustainability, improve yields, and reduce environmental impact. With the urgency for innovation greater than ever, AI is the essential lifeline the agricultural industry needs to secure a resilient and efficient future.