Agtools partnership with Procurant aims to help predict produce quality

Agtools
Agtools
(Graphic courtesy of Agtools)

Orange, Calif.-based Agtools has a new partnership with the software platform Procurant.

The partnership, leveraging advanced analytics and insights, can help streamline customers’ day-to-day activities around forecasting and purchase orders, according to a news release.

The system gives color-coded alerts to buyers and sellers based on USDA standards, and the phenological cycles of plants enable customers to view potential threats to crops before they arise and to quickly see the probability of receiving orders and the expected quality, according to the release.

“This partnership with Agtools supports our goal to enhance innovation and value for buyers and sellers of produce on the Procurant platform,” Ray Connelly, vice president of strategy for Procurant, said in the release. “By leveraging advanced analytics and insights, we can help streamline our customers’ day-to-day activities around forecasting and purchase orders.”

Agtools is the first third-party solution available through Procurant Connect, an application and services marketplace on the Procurant One platform, the release said. Procurant Connect allows users to integrate external data sources and features such as Agtools into their Procurant account.

With the Agtools add-on, users create a centralized hub for accessing up-to-the-minute commodity data, the release said. Agtools enables access to more than 70 types of commodity-specific information, including:

  • Pricing (fob, retail, terminal).
  • Volume statistics.
  • Weather analytics.
  • Quality metrics.


“Everyone in the industry is concerned about delivering or receiving commodities based on purchase orders,” Agtools CEO Martha Montoya said in the release. “With this partnership, Procurant and Agtools can bring unique, color-coded alerts to buyers and sellers based on USDA standards and the phenological cycles of plants. The alerts enable customers to view potential threats to crops before they arise, and to quickly see the probability of receiving orders and the expected quality.”

 

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