Brewing + AI Guidebook
How AI can help your brewhouse

Hold batches consistent

Use AI to spot drift in fermentation curves, temperatures, and pH against your own standard, so batch ten tastes like batch one.

Brewing + AI · practical use case

Consistency is what turns a good beer into a flagship. AI can watch your batches against your own baseline and flag when one is drifting, before the difference reaches the glass.

What it does

Compare a batch in progress, or just finished, against your standard for that beer and highlight where it deviates: a fermentation running hotter, a gravity finishing high, a pH out of range.

How it works, in brewing terms

It needs two things: a defined standard for the beer (your quality definition) and clean records to compare against it. With those, spotting an outlier is straightforward pattern work.

What you need to start

A written standard for the beer (see defining quality) and consistent batch records with the same fields captured every time.

Example prompt

"Here are my last 12 lager batches with fermentation temps and final gravities, and here is batch 13. Which of batch 13’s numbers fall outside the pattern of the previous 12?"

Keeping the brewer in control

The tool flags the drift; the brewer decides what to do about it. Adjustments to a live batch are always a human call.

Takeaways

Chapter 1 · Defining Quality Chapter 2 · Brew Data

Put this to work in your business

Ankur Napa spent a decade in breweries (AB InBev, SABMiller, United Breweries) before building AI and data tools for beer, wine, and spirits. Select consulting engagements in demand forecasting, quality and process analytics, dashboards, and production-grade GenAI.

Talk to a brewing data scientist →