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From Centuries-Old Brewing to AI-Driven Precision: How AB InBev Modernized Manufacturing with Google Cloud and Pluto7

A Decade of Impact: AB InBev Customer Story

For more than a century, beer brewing has relied on craft, consistency, and deeply ingrained processes. Even for a global leader like AB InBev, many critical manufacturing decisions especially on the shop floor were traditionally driven by human judgment, experience, and manual monitoring.

But as production scaled across geographies, one question became increasingly important:

How do you preserve quality and consistency while operating at global scale without increasing waste, downtime, or complexity?

As part of its broader digital transformation, AB InBev partnered with Pluto7 and Google Cloud to answer that question using applied AI operationalized through Pluto7’s Planning in a BoxPi Agent.

The Challenge: Modernizing a 100-Year-Old Process

At the heart of brewing lies a deceptively complex step: filtration.

During fermentation, beer contains residual particles that must be filtered out to achieve precise clarity or turbidity standards. Historically, this process depended on manual decisions made by operators balancing multiple variables at once:

  • Product quality targets
  • Equipment health
  • Energy usage
  • Production throughput

The margin for error was small. Over-filtering could lead to unnecessary waste and energy consumption. Under-filtering risked product quality. And unexpected equipment issues could cause unplanned downtime across the production line.

Scaling this decision-making consistently across dozens of breweries worldwide made the challenge even harder.

The Shift: From Manual Decisions to Machine Intelligence

AB InBev worked with Pluto7 to reimagine filtration as a data-driven, AI-powered decision process.

Using Google Cloud’s machine learning capabilities, and operationalized through Planning in a Box – Pi Agent, the team built models capable of running billions of simulations to understand how different variables impacted filter performance and beer clarity.

Rather than relying solely on human intuition, the system continuously evaluates:

  • Turbidity levels
  • Filter run conditions
  • Equipment behavior over time

This allows the brewery to predict when adjustments or maintenance are needed, optimizing each filter run while keeping machines operating longer.

In effect, decision-making moved from reactive to predictive.

The Role of Pluto7 and Google Cloud

Pluto7 brought deep expertise in manufacturing analytics and applied AI, while Google Cloud provided the scalable foundation required to operationalize these insights.

Planning in a Box – Pi Agent serves as the execution layer—embedding intelligence directly into day-to-day operations rather than keeping insights trapped in dashboards.

Together, they enabled:

  • Automated decision-making embedded directly into operations
  • Predictive analytics that reduce human error and accelerate response times
  • Cloud-based scalability, allowing innovations proven at one brewery to be deployed globally

Because the solution runs on Google Cloud, learnings from facilities like the Newark brewery can be rapidly extended across breweries in more than 26 countries.

The Impact: Efficiency, Quality, and Scale

The results of this transformation have been tangible and measurable:

  • Increased Equipment Uptime: Longer average filter runs enable higher production volumes
  • Reduced Waste: Optimized filtration minimizes energy usage and prevents loss of finished product
  • Consistent Quality: AI-driven control helps maintain uniform beer clarity and taste across regions
  • Scalable Innovation: Cloud-based deployment ensures consistent execution across global operations

What once required constant manual intervention is now guided by intelligent systems that learn and improve over time.

Beyond Brewing: A Blueprint for Industrial AI

For AB InBev, this initiative wasn’t just about improving a single process it demonstrated how legacy industrial environments can evolve using modern AI.

By replacing manual decision-making with predictive, data-driven intelligence, the company is proving that advanced AI can thrive even in highly physical, operational settings.

This approach aligns with AB InBev’s broader vision: delivering products faster, with higher consistency, while operating more sustainably.

Why This Story Matters

This collaboration reflects the core philosophy behind Pluto7’s work over the past decade:

AI delivers value only when it operates inside real decisions — not outside them.

Together with Google Cloud, Pluto7 helps organizations move from experimentation to execution embedding intelligence into the everyday flow of operations through platforms like Planning in a Box – Pi Agent.

As the first customer story in Pluto7’s Decade of Impact series, AB InBev’s journey illustrates what’s possible when applied AI meets deep domain expertise.

Looking Ahead

As manufacturers across industries seek greater resilience, efficiency, and consistency, the lessons from AB InBev’s transformation are increasingly relevant.

Cloud-based AI is no longer experimental. It is operational.

And for organizations ready to modernize without compromising quality, this story offers a clear path forward.

To learn more about how Pluto7 helps enterprises operationalize AI at scale, visit Pluto7.com.

Enable Decision Intelligence Into Every Corner Of Your Product And Operations.

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Industry Manufacturing

Platform Planning-in-a-box

Challenges

  • A critical filtration process depended on manual judgment, balancing beer clarity, equipment health, energy use, and throughput
  • Inconsistent decision-making increased the risk of waste, downtime, and quality variation
  • Scaling best practices across breweries in multiple countries was difficult and slow
  • Legacy processes made it hard to predict maintenance needs or optimize filter performance

Results

  • Extends filter run length, increasing production throughput and equipment uptime
  • Reduces filtration and energy costs by optimizing turbidity and filter conditions
  • Improves product consistency, delivering uniform beer clarity and taste across regions
  • Minimizes waste by preventing over-filtering and unnecessary product loss
  • Enables global scalability, allowing AI-driven decisions proven at one brewery to be deployed across 26+ countries
  • Accelerates decision-making, shifting from manual, reactive choices to predictive, data-driven operations

Products Used

  • Google Cloud Cortex Framework
  • Cloud Storage
  • Cloud Dataflow
  • Dataproc
  • BigQuery
  • Vertex AI
  • Cloud Functions
  • Cloud Build
  • Artifact Registry
  • Source Repositories
  • Secret Manager
  • Looker on Google Cloud
  • Looker Embedded Analytics
  • Cloud Identity and Access Management (IAM)
  • Cloud Key Management Service (KMS)
  • Cloud Data Catalog