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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 associated with the product is now CARL AI Gen. Traditionally, when a piece of equipment

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Domain-Specific Language BL.Optim

Solving optimization problem through the Domain-Specific Language based businesse rules modeler

BL.Optim is a research project of Berger-Levrault about planning management through optimization algorithm. However, the “constraints description” part in BL.Optim is supported by an API, which is extremely difficult to use to express new constraints. We want to replace the constraint descriptor by using a language more or less expressive, which allow us to easily

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Berger-Levrault and CNRS sign a strategic partnership

We have been working for many years with the CNRS. Dozens of CIFRE theses and collaboration contracts have enabled us to explore a very wide range of potential in the fields of artificial intelligence, sustainable cities, advanced human-machine interaction, automatic language processing, etc. This relationship, which is dear to us, has enabled the group to

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Intelligent document processing.

Active learning for intelligent document processing

Data is a key component of decision making. Today, companies deploy complex processes to automate the collection, storage and processing of large amounts of data. Most of this data is in the form of unstructured documents. Berger-Levrault’s software solutions handle documents of various natures: invoices, forms, etc. Unfortunately, this unstructured representation is difficult to exploit

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What are Emergent Software Systems about?

Nowadays, due to the constant evolution of the software systems’ operating environment, modern software systems become increasingly complex and larger which makes their management and evolution difficult for a development team. These challenges pushed the IT (Information Technology) community to develop solutions that aim to assign the responsibilities of adaptation and decision-making to the software

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BL.Assistant featured image.

BL.Assistant: Towards an Human-AI Teaming Platform

At work, you can have the best position ever (at least from your point-of-view), there are always boring and repetitive tasks to do that make you feel like you’re wasting your time. At Berger-Levrault, we aim to your life easier, that’s why we worked on BL.Assistant, a platform able to host AI-Based robots to assist

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Moose environment.

Visualize your codebase with Moose

Developing an application is teamwork. It requires complementary skills to make it run smoothly. Though, bugs happened frequently and it’s not easy to read the code and all its interdependencies. So the easiest way would be to call your colleague who worked on it, but he has a flu and can not answer you. To

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Thesis orals illustration 296px.

Pascal Zaragoza Ph.D. thesis defense: Model-driven migration of monolithic applications towards a microservice-oriented architecture

The passage to Cloud Computing fostered the development of new architectural styles to take advantage of its capabilities. The microservices oriented architecture (MSA) is the last style to emerge. This architecture is organized around small services focused on specifics business features, operating in independents processes and communicating through light interfaces. These features associated to cloud

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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,

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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

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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

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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

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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

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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,

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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

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