On May 29, 2025, the third edition of SmartEvent took place, spotlighting the latest advancements in CMMS and asset management. Co-organized by SMARTECH EAM Experts and CARL Berger-Levrault, the event brought together over 75 participants representing 45 companies, including maintenance professionals, AI specialists, and technology partners.
Renowned speakers, recognized for their expertise in industrial maintenance and emerging technologies, led the sessions. Among them was Youssef Miloudi, Director of BL.Predict at CARL Berger-Levrault, who shared a hands-on perspective on the application of artificial intelligence in predictive maintenance.
The event fostered insightful discussions, dynamic exchanges, and meaningful networking opportunities. Attendees expanded their knowledge, explored cutting-edge industry innovations, and forged lasting connections in an environment designed to encourage collaborative learning and the sharing of expertise.
Introduction of Smartech EAM Experts
The day began with a welcome address by Mr. Mohamed Skandaji, Director of Smartech EAM Experts, who expressed his gratitude to the participants for attending this event dedicated to innovation and knowledge sharing.
The introduction was followed by a presentation of Smartech EAM Experts, a company specializing in services, consulting, integration, and development in the field of asset management and maintenance, with expertise in IBM Maximo EAM and CARL Source solutions.
Smartech supports clients across four continents, helping them implement high-performance asset management programs that leverage the latest technological advancements.
As an official partner of IBM and CARL Berger-Levrault, Smartech capitalizes on these strategic alliances to deliver tailored, high-value solutions. These partnerships ensure broad functional coverage, smooth integration with existing systems, and deep expertise across the entire asset lifecycle.
CARL Source: A CMMS Designed for Today and Ready for Tomorrow
The event opened with an in-depth look at CARL Source, the CMMS solution developed by CARL Berger-Levrault. Modular, robust, and scalable, this platform has become a benchmark in optimizing equipment, work orders, and technical resource management.
Natively built for web architectures and integrating the latest technologies, CARL Source merges innovation with an intuitive user experience to meet the evolving needs of modern organizations. Offered as a traditional on-premise license or through secure SaaS hosting, the solution allows for flexible deployment.
CARL Source offers a comprehensive suite of business functionalities, further extendable through complementary modules:
- Maintenance Management: Plan, execute, and monitor preventive and corrective maintenance, manage requests, work orders, schedules, and historical data.
- Asset Management: Track the status, location, and maintenance history of equipment, buildings, and infrastructure.
- Inventory Management: Oversee spare parts, stock levels, inventory movement, and orders to streamline the supply chain.
- Cost Monitoring: Analyze maintenance expenses, including labor, parts, and energy, using customizable reporting tools.
- Planning & Reporting: Leverage advanced planning capabilities, dashboards, and KPI tracking for better decision-making.
- Mobile Capabilities: Enable field teams to access real-time data, update work status, and consult technical documents via smartphones or tablets.
With this solution, CARL Berger-Levrault provides a true performance enabler, combining robust functionality with a modern user experience to empower maintenance teams.
Artificial Intelligence: From Concept to Impact
Artificial Intelligence (AI) is transforming maintenance, driving a shift from reactive approaches to proactive and predictive strategies. These technologies now deliver tangible operational and economic benefits.
One of the event’s highlights was a session led by Youssef Miloudi, Director of BL Predict at CARL Berger-Levrault. He offered real-world examples of how AI is already being used to predict failures, optimize scheduling, and reduce operational costs, while increasing asset availability.
The effectiveness of these innovations is backed by industry research. According to McKinsey’s 2024 State of AI report:
- 72% of organizations identify cost reduction and process optimization as top priorities
- 51% aim to improve operational responsiveness
Solutions like CARL Predict, CARL AI.Gen, and CARL Optim directly support these objectives:
- CARL Predict uses IoT sensors and machine learning to anticipate equipment failures before they happen.
- CARL AI.Gen allows technicians to dictate interventions, which are automatically transcribed and integrated, accelerating decision-making.
- CARL Optim creates optimized maintenance schedules in minutes, factoring in complex constraints for efficient field operations.
These solutions deliver concrete benefits:
- Reduced downtime via faster diagnostics and proactive interventions
- Optimized processes through intelligent planning and data usage
- Lower operating costs thanks to automation, fewer errors, and upskilled teams
AI has firmly established itself as a strategic lever in today’s data-driven maintenance landscape.
Product Innovations: CARL Source at the Forefront
The product roadmap for CARL Source was also revealed, showcasing upcoming enhancements in ergonomics, redesigned mobile interfaces, and expanded interoperability with IoT, BIM, ERP, and other systems,responding to increasing user demand for intelligent, connected, and user-centric CMMS tools.
Spotlight on BL.Predict: Anticipate to Perform Better
The event concluded on an innovative note with the presentation of BL.Predict, a cutting-edge, data-driven platform for optimizing equipment performance.
This next-generation solution integrates IoT sensors, advanced analytics, and machine learning to maximize asset performance, extend equipment lifespan, and promote sustainable infrastructure management.
Designed as a smart interoperability platform, BL.Predict seamlessly connects with Atal, CARL Source, and third-party CMMS tools. It collects, stores, and analyzes field data to generate contextual, high-value predictive maintenance insights.
Proven impact includes:
- +15% improvement in maintenance operations
- –25% reduction in operating costs
- –15% in energy consumption
- +10% increase in equipment lifespan
- +20% boost in asset productivity
By leveraging collaborative intelligence and federated learning, BL.Predict locally processes sensor data (from LoRa networks, field systems, etc.) to deliver actionable dashboards and detect critical events and anomalies.
Its predictive power is based on historical faults, usage cycles, and production anomalies, allowing teams to act precisely when and where it matters.
BL.Predict is structured around three core modules:
- Smart: Real-time monitoring of key operational indicators
- Facility: Anomaly detection via predictive AI models
- Efficiency: Behavioral analysis for fine-tuned preventive maintenance
These capabilities allow maintenance teams not only to understand when, how, and why failures occur,but also to receive actionable recommendations: equipment adjustments, environmental adaptations, energy-saving actions, and more.
Interoperable, intelligent, and high-performing, BL.Predict opens the door to more effective, sustainable, and connected maintenance, ensuring business continuity and energy efficiency.
Conclusion
The May 29 event underscored the strategic importance of technology in transforming maintenance. From AI-driven innovation to next-generation CMMS tools and predictive platforms like BL.Predict, the future of asset management is becoming smarter, more agile, and more efficient than ever. To receive the full event recap, please submit your request here.
