Mid-Iowa Cooperative is a member-owned agricultural company that works with farmers across central Iowa. Like many ag businesses, they handle a lot of transactions, which require thorough documentation. They noticed they were spending too much time on manual data entry, especially on the processor settlement documents that record transactions with farmers and other local vendors.
Each settlement statement contained pages of detailed information about loads coming in and out of the co-op. Mid-Iowa staff used to have to manually rekey those details into internal systems—a time-consuming, error-prone process.
To solve this challenge, Mid-Iowa partnered with Far Reach to develop a custom AI solution that automatically extracts and organizes data from settlement PDFs. They’re now saving hours of manual work and have fewer data errors.
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The Challenge: Time-Intensive Manual Entry
Before implementing AI automation, Mid-Iowa’s team handled each settlement document manually. Each statement—often 10 to 20 pages long—contained key data points like product type, quantities, and pricing details.
Every page included 10 to 15 fields of data and up to 20 rows per page, resulting in hundreds of data fields per statement. Processing these by hand was slow and tedious, and it left room for human error.
Mid-Iowa needed a solution that could:
- Read and extract structured data from different PDF templates
- Organize the information into a standardized format
- Upload the organized information into their internal systems
- Scale to add more vendors
Their existing internal system had limited AI capabilities, so they turned to Far Reach for a custom-built approach.
The Solution: A Custom AI Model for Document Intelligence
Far Reach developed an AI-powered data extraction system tailored to Mid-Iowa’s settlement workflow.
The process begins when a team member uploads a vendor’s settlement PDF to a shared Azure storage folder. From there, the custom AI engine takes over and:
- Reads and interprets the settlement document
- Extracts key data fields (such as load weights, dates, and prices)
- Exports the structured data into a spreadsheet for import into Mid-Iowa’s ERP system
Each vendor has its own trained model and dedicated output folder, allowing the AI to handle multiple document types with high accuracy.
The system was built using Microsoft Azure AI Document Intelligence as a foundation. We then trained and customized models for each vendor’s specific PDF format, teaching the AI where to locate each field of data and how to format it for output.
We also implemented validation scripts and a test suite to ensure accuracy. This process essentially runs each sample document against expected results to confirm the AI performed as intended.
The Results: Fewer Hours, More Accuracy
Since implementing the new system, Mid-Iowa has seen a significant reduction in manual data entry.
“It depends on a lot of factors, but we save at least a few hours per day compared to manual entry,” said Joel Benson, IT Director at Mid-Iowa Cooperative.
Instead of typing information from every PDF into Excel by hand, staff now upload the PDFs and let the AI do the heavy lifting. The automated process reduces errors and helps the team process settlements faster, which can lead to quicker payments for farmers and vendors.
“It’s nice to have AI help solve a real problem,” said Benson. “We came to Far Reach with examples of what we needed, worked through them together, and got a great solution. The team has been knowledgeable, responsive, and easy to work with.”
A Practical Use Case for AI in Agriculture
The success of this project has opened new doors for Mid-Iowa. The team is exploring ways to expand AI-based document processing to additional vendors and document types. They now have a flexible foundation that can grow with their needs.
The goal of AI in custom software development is to use smart, targeted technology that simplifies workflows. For Mid-Iowa, that meant turning a time-consuming manual process into an efficient, automated workflow that saves time, improves accuracy, and enables their team to focus on higher-value work.
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