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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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Neolink: Lifelong pathway recommendation challenges

Neolink is a company created in 2012 which developed solution to encourage the internet that brings together. Its main objective is to unify economic activity and social utility in its solutions. The company has been bought by Berger-Levrault in 2019. Social services are notoriously complex to model and manage. It is essential to turn to

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3D Big data in modern city. Abstract social information sorting visualization. Human connections or urban financial structure analysis. Complex geospatial data. Visual information complexity.

Equipment 3D visualization in a CMMS application-1st part

Computer-aided maintenance systems aim at assisting administration and maintenance agents in their missions of assets maintenance (building, network, air conditioning, faucets, etc). Assets may have different representations in different geospatial data sources (2D or 3D) that can help to have a better understanding of them by providing new information. Though, using those data often leads

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Mono2Micro-MDE : An end-to-end approach towards migrating a monolithic application towards a microservice-oriented architecture

Find the first migration approach in these articles: article 1 & article 2 In this section, we introduce a broad overview of the different phases which constitute our global MDE-based migration workflow. In short, our workflow (see Figure 1) encompasses 4 important steps : Extracting a model from the source application. Identifying the application’s candidate

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Image analysis for Maintenance intervention request classification

Technologies and systems for automation of maintenance tasks and equipment management are used in several cases of different business fields like security or food-processing industry for instance. The technologies used have reached a maturation stage allowing their use in real case, according to practical application specificity. However, it remains uncertainties about developing an approach allowing

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Backend monolithic app to microservices architecture migration – 2nd part

Find the first part of the article by following this link In the first part article, we’ve explained how to identify microservices candidates by extracting the layered architecture artifacts from the existing code of a monolithic application. Several approaches address this first step, though they either do not address the materialization step or complete this

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BL.Conecta, the future kernel of city’s intermediation platforms?

Context Since few years, we observe the rise of intermediation platforms and web services consumption used through these multitude of platforms. The fact is that intermediation environments put in relation a producer/seller with a web user/consumer to enable a transaction (sales, exchange, share of products or services) that create value. Intermediation platforms are used as

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Backend monolithic app to microservices architecture migration – 1st part

Generally, companies software are built in a three part system: a client side/user interface, a database, and a side-server application called a monolith. Monoliths are often built as a single logical executable, in a single-tiered with multiple layers: presentation, business logic, and data-access. These apps are easy to design and develop, though they are difficult

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Maintenance queries classification with NLP

When our client equipment needs maintenance intervention for any reason, they can request it through Carl Source, our CMMS software. Those intervention queries will be received by the technical service which will analyze it, pre-qualify it and associate it to an intervention type before scheduling it. Some interventions are more urgent to other and some

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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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