Latest articles
Airflow: feedback on BL.Predict and Foundation use cases
Introduction In a context where the automation of data workflows has become a fundamental pillar of project reliability and scalability, Apache Airflow has established itself as an essential tool within the technical ecosystem of our BL Research team, dedicated to Research and Technological Innovation at Berger-Levrault. Whether orchestrating text document processing chains or driving transformations on IoT data, Airflow offers invaluable flexibility when properly mastered. Two use cases embody our
Applying Agentic AI towards enabling computerized maintenance management systems
In the critical domain of Computerized Maintenance Management Systems (CMMS), solutions like CARL Source empower businesses to efficiently create, schedule, and manage maintenance tasks. These platforms are widely used to coordinate work orders for repairing industrial machinery across multiple factories worldwide. *Update: Coruscant is the name given internally to this R&D project. The commercial name
Enhancing Domain-Specific RAG Applications through Synthetic Fine-Tuning
Keywords: Synthetic Data, Retrieval-Augmented Generation (RAG), Small Language Models (7B LLM), Large Language Models (LLM like GPT-4o or GPT4.5), Model Adaptation, Efficient Model Tuning, Low-Resource Fine-Tuning, Synthetic Fine-Tuning. 1. Introduction In the context of our Research & Innovation efforts at Berger-Levrault, we are exploring how large language models (LLMs) can enhance customer support through intelligent,
Hamza Safri Ph.D. thesis defense: “Federated learning for the IoT : Application for Industry 4.0”
Thuesday 24th June at 3pm Paris time, Hamza Safri, Ph.D. Candidate has defended his thesis named “Federated learning for the IoT: Application for Industry 4.0”. His thesis defense took place at the Inria Minatec Grenoble, Grenoble, France. Take a look at the summary below. Keywords: Model generalization, predictive maintenance, industrial IoT, federated learning, edge network,
Success Story BL.Predict x Saint Jean: challenges and benefits of switching from corrective to preventive maintenance
Success Story BL.Predict x Saint Jean! The objective? Optimize the maintenance of its fresh pasta production! Production line availability, data centralization, migration from corrective to preventive maintenance… Here’s a look back at this collaboration which combines technological innovation and complex manufacturing systems. La “Maison” Saint Jean, the art of fresh French pasta History shows that
New White Paper – AI for maintenance! Challenges, Opportunities and Case Studies
How is artificial intelligence transforming maintenance practices today? What are the concrete opportunities for equipment, infrastructure and fleet managers? The new white paper published by CARL Berger-Levrault offers a rich and accessible insight into these strategic questions. Entitled “AI at the service of maintenance: challenges, opportunities and case studies”, this document summarizes experience in the
Towards a Human-Like Evaluation: Innovations, Applications, and Future Directions
In his previous article, Romain explored the theoretical foundations and methods dedicated to the automatic evaluation of artificial intelligence systems, emphasizing the importance of making them more human and intuitive. This article continues this reflection by focusing on the practical applications of these advances. How are these innovations deployed? What challenges do they face? What
New White Paper – Agentic AI, a Software and Societal Revolution!
Research at Berger-Levrault is tackling a new frontier in artificial intelligence: that of (partially) autonomous agents capable of reasoning, planning, collaborating, orchestrating and learning in complex business environments. Our new white paper, “Beyond automation – How agentic AI is transforming the software industry”, shares with you an in-depth analysis of this ongoing technological revolution, its
Re.Optim: Responding dynamically to changes and unforeseen events in schedules generated by BL.Optim
BL.Optim: A cutting-edge but static planning optimization tool BL.Optim is our optimization engine for routing and scheduling, used to generate efficient planning under complex constraints. While highly flexible, it currently operates as a static solver: schedules are generated once, based on a submitted problem, and cannot be adapted without full recomputation. When plans need to
Clément talks at BIM World 2025 on the future of augmented maintenance using BIM models
At BIM World 2025, held in Paris on April 2-3, Clément Colin, our research engineer in BL Research team, spoke at a workshop dedicated to Digital Twins, alongside Laurent Truscello, Product Marketing Manager at Carl Berger-Levrault. The theme of their talk: “GEM & GMAO – Valuing and increasing the use of your BIM models for
Some Berger-Levrault Living Lab Uses Cases: a Valuable Tool to Understand Users in Real Situations
This article by Valérie follows on from a previous one describing the innovative Living Lab set up at Berger-Levrault. As a reminder, this innovative, user-centered approach aims to optimize the development of appropriate, useful solutions that respond directly to the real needs and challenges encountered in the field by customers and users of our software.
36th International Conference on Database and Expert Systems Applications – DEXA 2025 (Bangkok – Thailand)
20th International Conference on Software Technologies – ICSOFT 2025 (Spain)
CIFRE Strategic orientation committee x ANRT (Paris – France)
Regional morning: Transforming maintenance into a profit center x Swarm itc and AFIM (Charbonnières Les Bains – France)
9th International Workshop on Green and Sustainable Software – GREENS’25 (Ottawa – Canada)
Hamza Safri Ph.D. thesis defense: “Federated learning for the IoT : Application for Industry 4.0”
Thuesday 24th June at 3pm Paris time, Hamza Safri, Ph.D. Candidate has defended his thesis named “Federated learning for the IoT: Application for Industry 4.0”. His thesis defense took place at the Inria Minatec Grenoble, Grenoble, France. Take a look at the summary below. Keywords: Model generalization, predictive maintenance, industrial IoT, federated learning, edge network,
ESUG 2025: Six contributions and 2 prizes for the Software Engineering Lab team!
Congratulations to our PhDs Nicolas Hlad, Aless Hosry, Benoit Verhaeghe and Pascal Zaragoza from Berger-Levrault’s BL.Research team for their participation in the 2025 edition of the ESUG (European Smalltalk User Group) conference! This year’s conference took place from July 1-4 in Gdansk, Poland. The theme was innovation in Smalltalk technologies and their use in software
Julien Breton Ph.D. thesis defense: “Extraction and formalization of regulatory industrial maintenance knowledge from semi-structured corpus data”
Friday, 27th June at 1.30 pm Paris time, Julien Breton, Ph.D. Candidate has defended his thesis named “Extraction and formalization of regulatory industrial maintenance knowledge from semi-structured corpus data”. His thesis defense took place at the IRIT research laboratory, Toulouse, France. Take a look at the summary below. Keywords: Legal compliance,Industrial maintenance, Norm extraction,LLM (Large
New White Paper – AI for maintenance! Challenges, Opportunities and Case Studies
How is artificial intelligence transforming maintenance practices today? What are the concrete opportunities for equipment, infrastructure and fleet managers? The new white paper published by CARL Berger-Levrault offers a rich and accessible insight into these strategic questions. Entitled “AI at the service of maintenance: challenges, opportunities and case studies”, this document summarizes experience in the
New White Paper – Agentic AI, a Software and Societal Revolution!
Research at Berger-Levrault is tackling a new frontier in artificial intelligence: that of (partially) autonomous agents capable of reasoning, planning, collaborating, orchestrating and learning in complex business environments. Our new white paper, “Beyond automation – How agentic AI is transforming the software industry”, shares with you an in-depth analysis of this ongoing technological revolution, its
Clément talks at BIM World 2025 on the future of augmented maintenance using BIM models
At BIM World 2025, held in Paris on April 2-3, Clément Colin, our research engineer in BL Research team, spoke at a workshop dedicated to Digital Twins, alongside Laurent Truscello, Product Marketing Manager at Carl Berger-Levrault. The theme of their talk: “GEM & GMAO – Valuing and increasing the use of your BIM models for
From the Iberian sun to the Rising sun for federated learning
On September 2024, we had the opportunity to attend two international conferences related to a segment of our work in artificial intelligence : Data Training Without Perturbative Adjustments for Predictive Maintenance The FLTA24 took place from September 17 to 19 in Valencia, Spain. As part of this research, we studied a concrete case: predictive maintenance,
Discover our 2024 Research & Innovation Yearbook!
We are delighted to present the first edition of the Research and Innovation Yearbook. This annual retrospective reflects the commitment and ambition of our Research and Technological Innovation Department at Berger-Levrault (also available in French and Spanish versions below). By highlighting our most audacious projects and innovative initiatives, we hope to share with you the
