Smarter Water Treatment Starts With Insight
Detect inefficiencies, optimize chemical dosing, and prevent equipment issues — with AI that enhances compliance and process stability.
Short Description
Water treatment facilities must balance performance, safety, and regulatory compliance — often across aging infrastructure and fluctuating demand. From filtration and disinfection to sludge processing and chemical dosing, every process step must be tightly controlled.MontBlancAI equips plant operators with real-time visibility, early anomaly detection, and intelligent alerts — helping you reduce downtime, lower operational costs, and ensure consistently safe water delivery.
Challenges
What's Holding Your Operations Back?
In today's fast-paced production environments, identifying and addressing operational challenges is crucial for maintaining efficiency and competitiveness. From manual processes that slow down root cause analysis to high energy consumption that inflates costs, these hurdles can significantly impact productivity.
Energy costs can constitute up to 60% of a wastewater treatment plant's operational expenses, with pumping systems being the primary energy consumers.
Data-driven Predictive Energy Optimization in a Wastewater Pumping Station – arXiv
Urban water utilities in North America lose approximately 20–30% of treated water through leaks in aging infrastructure.
Water Industry Statistics: Reports 2025 – WiFiTalents
Manual root cause analysis can take up to 5 days per incident, delaying resolution and increasing production risk.
Industry interviews & studies
Benefits
Unlock Smarter Production
Transform your operations with AI-powered insights and automation
Deeper Operational Insights
Uncover trends and patterns with advanced analytics tailored to manufacturing processes.
Higher Data Accuracy
Ensure precision in production tracking with automated and validated data collection.
Instant Alerts & Notifications
Receive automated alerts the moment anomalies or threshold violations occur.
Cross-Functional Collaboration
Break silos by enabling real-time collaboration across teams and locations.
End-to-End Traceability
Track materials, batches, and processes across the full production chain — from input to output.
Platform
How Our Platform Optimizes Your Production
Track & Trace
Ensure product quality and compliance with end-to-end batch tracing. Quickly and easily trace defective products back to their sources with historical data from batch tracing.
AI-Powered Analytics
Machine learning models analyze batch data to identify patterns and predict quality outcomes.
Real-Time Monitoring
Continuous tracking of production parameters with instant visibility across all stages.
Compliance Automation
Automated documentation and audit trails for regulatory requirements.
AI-Powered Analytics
Machine learning models analyze batch data to identify patterns and predict quality outcomes.
Real-Time Monitoring
Machine learning models analyze batch data to identify patterns and predict quality outcomes.
Compliance Automation
Machine learning models analyze batch data to identify patterns and predict quality outcomes.
Instant Recall
Machine learning models analyze batch data to identify patterns and predict quality outcomes.
CIP Validation
Validate your CIP (Clean-in-place) or production cycles in mins (not hours) with just a few clicks.
Cycle Analytics
Deep analysis of every CIP cycle to identify optimization opportunities.
Anomaly Detection
AI identifies deviations from standard cleaning patterns before they cause issues.
Auto-Optimization
Automatically adjusts cycle parameters based on historical performance data.
Cycle Analytics
Deep analysis of every CIP cycle to identify optimization opportunities.
Anomaly Detection
AI identifies deviations from standard cleaning patterns before they cause issues.
Auto-Optimization
Automatically adjusts cycle parameters based on historical performance data.
Validation Reports
Generate compliance-ready validation reports with a single click.
Threshold Alerts
Let our AI-powered anomaly detection algorithms identify faults in your production process. Get instant notifications when issues arise so you can take immediate action and minimize waste.
Smart Notifications
Context-aware alerts that prioritize by severity and potential impact.
Predictive Warnings
AI predicts potential threshold breaches before they occur.
Trend Analysis
Visualize parameter trends to understand patterns and prevent issues.
Smart Notifications
Context-aware alerts that prioritize by severity and potential impact.
Predictive Warnings
AI predicts potential threshold breaches before they occur.
Trend Analysis
Visualize parameter trends to understand patterns and prevent issues.
Instant Response
Trigger automated responses when critical thresholds are crossed.
Case Studies
How Leading Companies Transform their Operations
Real-world examples of operational excellence achieved through our platform
Identifying Defects Early
A huge range of issues has the potential to delay, disrupt, and derail manufacturing operations. If you can identify these issues at the earliest opportunity, you can maintain an efficient production process. Traditional monitoring methods struggle to pick up issues such as performance deviations, short-term disruptions, and the failure of critical components such as filtration membranes. Our approach to predictive solutions provides a proven answer to this problem.
Optimize Dairy Production
Germany is home to one of the world’s most competitive dairy industries. The small and moderately-sized dairies in the country have to take every opportunity to make their operations more efficient and productive. This is a cost-effective and reasonably feasible way to compete with the large corporations. The pursuit of efficiencies and increased capacity plays a crucial role in this process, but traditional assessment methods are costly, time-consuming, and relatively unreliable.One relatively small dairy approached us due to our reputation for powerful production process monitoring software. The brief was simple: To decide whether optimizing existing equipment or investing in new machinery was the most cost-effective way forward.
UF System Optimization
A major production facility approached us to address the operational issues behind a significant downtime rating. When the facility’s management first assessed the situation, the maximum continuous runtime was a paltry 13 hours before a Cleaning-in-Place cycle was needed. The relatively low uptime witnessed was having a seriously detrimental impact on both operational efficiency and capacity. With the help of MontBlancAI, the team implemented a series of targeted optimizations using, among other things,AI-powered operational intelligence tools. As a result, the facility significantly increased overall efficiency and capacity. Here’s how they did it with the help of our cutting-edge operational intelligence tools.
Enhanced OEE
A manufacturing facility was struggling with filling line inefficiencies, despite seemingly stable monthly performance reports. Frequent, untracked short stops and unclear performance fluctuations were silently eroding productivity. By leveraging MontBlancAI’s advanced production monitoring tools, the facility uncovered and addressed these issues, delivering a remarkable 12.4% increase in Overall Equipment Effectiveness (OEE) within just six weeks. This case study details the challenge, the innovative approach, and the eventual results.
Continuous CIP Validation
Monitoring and validating Clean-in-Place (CIP) processes can be a complex, time-consuming, and costly process, particularly for relatively modest operations. However, production intelligence software powered by AI can make it significantly easier. That’s why a German dairy, processing more than two million liters of milk, turned to MontBlancAI for help. Producing high-quality milk, cream, yogurt, cheese, and butter, the dairy relies on CIP to clean and sanitize equipment and pipelines, ensuring product hygiene, quality, and safety.Was there a way to streamline and enhance the existing CIP processes? Let’s take a look.
