Findability Sciences introduces LactaAI to boost dairy processing

USA – Findability Sciences has introduced LactaAI, an artificial intelligence platform for dairy processing that helps plants identify developing yield loss and act while the problem can still be corrected.

LactaAI connects information from the plant floor, laboratory, and enterprise systems. It works with existing PLC, SCADA, ERP and LIMS environments, so processors do not need to replace their current infrastructure or add sensors to get started. Customers retain ownership of their process data.

Within LactaAI is Lacta Insight, which gives plant teams a live view from reception to packaging, and Lacta BPC, which supports documentation, enterprise knowledge, and business workflows through a conversational interface.

Lacta Insight follows six connected steps: Detect, Explain, Diagnose, Recommend, Act and Measure. Each recommendation includes the reasoning behind it and can include a confidence score and projected effect. The operator decides whether to act, and the system records every decision for review and audit.

The platform currently supports butter, milk powder, and milk protein concentrate and whey lines. It can also be configured for cheese and other dairy processes. A processor can start with one priority line and expand to other processes without rebuilding the core system each time.

According to the company, dairy plants collect vast amounts of information across milk intake, processing, quality, utilities and business systems, and answers to inefficiencies are spread across different systems.

A single alarm may show that something has changed, but it does not explain how the signals connect or what the team should do next. By the time the team connects the signals and identifies the cause, the loss may already be affecting yield and margin.

The scale of USA dairy processing makes that delay expensive. The US Department of Agriculture estimates that the country produced 231.7 billion pounds of milk in 2025.

At that volume, even a modest improvement in recovery can create meaningful value. For example, for every 100 million pounds of annual finished product volume, a 1% to 2% increase in recovery can represent roughly 1 million to 2 million additional pounds of saleable product.

 Depending on the product, that could represent $1 million to more than $5 million in additional annual product value.

“Dairy plants have never lacked signals. The challenge is catching and understanding them early enough for the response to matter,” said Anand Mahurkar, founder and CEO of Findability Sciences.

“LactaAI connects what is happening across the line and helps the team act before a small shift becomes lost product. That is the difference between finding a problem in yesterday’s report and protecting margin while the line is still running.”

Across dairy manufacturing, artificial intelligence used for process optimization has been associated with faster root cause investigations, lower solids loss, fewer quality deviations and reduced energy use.

Findability Sciences cites industry benchmarks and engineering estimates that indicate potential improvements of 70-90% in investigation time, 3-4% in avoidable solids loss, 20-40% in quality deviations and 5-8% in steam and energy consumption, depending on the plant.

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