Making sense of livestock data with AI-powered chatbot Calvin

Amino, MTech Systems' food production and agricultural supply chain software, is about to revolutionize the way livestock data is presented. With the help of AI-powered chatbot Calvin, food producers will gain insights into their operations in ways previously unimaginable.

Amino is an easy-to-use cloud-based food supply chain software that covers all performance, costing, and planning needs. By having all data in one place, food producers can easily understand what drives better flock performance.

As AI improves, so do the possibilities for Amino to become even more useful for food producers and other actors in the food supply chain such as farmers and feed mills.

“By leveraging Azure OpenAI, we are elevating data presentation to an entirely new level,” says Barry Schulz, CTO at MTech.

Barry and his team recently developed the very first version of Calvin, a chatbot that can ingest large volumes of Amino's data to present insights in ways previously unimaginable.

“Calvin has access to our extensive documentation, database information, code, etc” Barry explains. “This allows our team members to ask questions and receive answers that would traditionally require a software developer or business analyst.”

With just a simple prompt from a user, Calvin triggers its AI agents to perform various tasks at remarkable speeds. These agents can retrieve information, create content, translate data, package it, and even email it – all in a matter of seconds.

“These AI agents work together seamlessly to unlock the full potential of our data,” Barry says. “By leveraging natural language processing and machine learning capabilities, they can pinpoint statistical anomalies, generate detailed visualizations, and even provide predictive analytics. The possibilities are truly impressive.”

The AI agents not only process inquiries but also write and execute code to deliver comprehensive answers. “Thanks to Calvin, our customers can delve deeper into their data, moving beyond basic troubleshooting to gain more insightful and engaging experiences,” Barry adds.

The ultimate goal is to automate routine tasks such as data entry and validation using AI.

“For example, by integrating Document Intelligence, we can automatically extract and validate information from various documents, eliminating manual data entry,” Barry explains.

Barry continues, “By removing all the data entry, we increase productivity and free up time for users (customers and their staff) to focus on more value-added activities. As soon as our customers begin using Calvin, they will find the bot so beneficial that they will want ask numerous questions to gain deeper insights into their operations.”

About Barry Schulz:

• Has a bachelor's degree in computer engineering
• Joined MTech 20 years ago
• Resides in Atlanta, Georgia
• Enjoys hanging out with my family, home projects, watching live music and learning new things