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Features

Discover our platform's capabilities.

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Connect with your existing systems.

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Case Studies

CIP Validation

A Dairy-Based Success Story

Optimizing Dairy Production

Data-Driven Insights Powered by AI

Identifying Membrane Defects Early

The Power of Intelligent Manufacturing Solutions

Enhanced OEE

10% Uplift for a Filling Machine

UF System Optimization

70% Uptime Increase

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Learn more about AI in manufacturing.

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The Central Intelligence Hub for Process Manufacturers

Increase production capacity  |  Reduce operating cost  |  Ensure quality  |  Fight labor shortage

Connect. Understand. Optimize. Across Every Layer.

Your Central Intelligence Hub

MontBlancAI acts as the brain of your production ecosystem - ingesting data from sensors, PLCs, SCADA, MES, and ERP systems to create a unified operational intelligence layer. No more data silos.

Unified Data Layer

Connects PLCs, SCADA, MES & ERP into a single intelligence layer.  Cleans data for you.

Actionable Insights

From dashboards to root cause diagnostics. All powered by AI.

Real-Time Anomaly Detection

Finds anomalies before they disrupt production. Beyond traditional thresholds.

Testimonials

Why our customers love MontBlancAI

"The integration of MontBlancAI was very smooth. Onboarding was quick and the automatic validation of our process data helped us win a big customer."

San Gregorio

"In just a few steps, we were able to see the utilization of our systems. With just one glance, we can analyze and compare the efficiency of our production over days and weeks."

Marecuador

"MontBlancAI is our digital twin for production processes, supported by AI-based applications. It seamlessly integrates our process data with ERP, MES and SCADA."

Naabtaler Milchwerke

Case Studies

CIP Validation

Dairy Production

Early Defects

Enhanced Equipment

UF Optimization

Monitoring and validating Clean-in-Place (CIP)processes can be a complex, time-consuming, and costly process—particularly forrelatively modest operations. However, production intelligence software poweredby AI can make it significantly easier. That’s why a German dairy, processingmore than two million liters of milk from more than 2,000 farmers, turned toMontBlanc for help.  Producing high-quality milk, cream, yogurt,cheese, and butter, the dairy relies on CIP to clean and sanitize equipment andpipelines, ensuring product hygiene, quality, and safety.
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Germany is home to one of the world’s mostcompetitive dairy industries. The small and moderately-sized dairies in thecountry have to take every opportunity to make their operations more efficientand productive. This is a cost-effective and reasonably feasible way to competewith the large corporations.  The pursuit of efficiencies and increasedcapacity plays a crucial role in this process, but traditional assessmentmethods are costly, time-consuming, and relatively unreliable.
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A huge range of issues has the potential todelay, disrupt, and derail manufacturing operations. If you can identify theseissues at the earliest opportunity, you can maintain an efficient productionprocess.  Traditional monitoring methods struggle topick up issues such as performance deviations, short-term disruptions, and thefailure of critical components such as filtration membranes.  Our approach to intelligent manufacturingsolutions provides a proven answer to this problem.
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A major production facility approached us toaddress the operational issues behind a significant downtime rating. When thefacility’s management first assessed the situation, the maximum continuousruntime was a paltry 13 hours before a Cleaning-in-Place cycle was needed. The relatively low uptime witnessed was havinga seriously detrimental impact on both operational efficiency and capacity.
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A manufacturing facility was struggling withfilling line inefficiencies, despite seemingly stable monthly performancereports. Frequent, untracked short stops and unclear performance fluctuationswere silently eroding productivity.  By leveraging MontBlancAI’s advancedoperational intelligence tools, the facility uncovered and addressed theseissues, delivering a remarkable 12.4% increase in Overall EquipmentEffectiveness (OEE) within just six weeks. This case study details the challenge,the innovative approach, and the eventual results.
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