AI-enabled spectrometry is a method for performing multiple brewing water and beer analyses automatically and in near real-time.

This process combines traditional spectrometry with artificial intelligence to interpret light passing through a liquid sample. The AI component processes the data and provides both qualitative and quantitative results without requiring the user to interpret complex spectrographs.

A single optical scan can determine several key factors, including brewing water type, pH, beer color, bitterness, and alcohol content.

Compared to traditional lab testing — which often involves multiple instruments, reagents, and trained technicians — AI-enabled spectrometry offers a streamlined approach. It reduces the time needed for results while maintaining accuracy and reliability.

As this technology continues to advance, it has the potential to expand access to detailed brewing analysis, supporting better decision-making and quality control in a variety of brewing environments.

Sydney Sukuta holds a PhD in chemical physics, is the principal at Sukuta Technologies LLC, and has been a professor of physics and laser technology at San Jose City College for more than two decades now.

He has two issued US patents in the artificial intelligence, ai, space, and has others pending. He is focused on the application of ai for lab and process real-time tests and automation for efficiency, reliability and accuracy.