Artificial Intelligence and Algorithms for Industry
Accelerating industrial transformation through integrated, applied, high-performance, and trusted AI
Our approach aims to transform advances in AI into practical, robust solutions that are integrated into real-world environments.
By combining scientific expertise, deep industry knowledge, and systems engineering capabilities, we help organizations address performance, reliability, and scalability challenges.
AI Built Around Real Business Applications
Our work covers a wide range of approaches, from traditional predictive analytics to the latest generative AI technologies.
We operate in demanding application environments, including telecommunications, industrial maintenance, digital health, robotics and cobotics, human factors analysis, and defense.
Our teams contribute both to operational developments and advanced research programs, with the aim of anticipating technological advancements and accelerating their commercialization.
Four Areas of Expertise in Applied AI
| Area | Objective | Core Capabilities |
| Predictive AI & Optimization | Detect weak signals, anticipate failures, and optimize real-time decision-making in complex environments. |
Machine learning |
| Generative AI & Knowledge Engineering | Structure, leverage, and extract value from complex data using generative models and intelligent agent orchestration. | LLMs Multimodal AI RAG architectures Embeddings Vector databases Intelligent agents Human-machine interaction |
| Data, Signals & Applied Mathematics | Understand what data reveals—and what it does not—before training any model, starting from the acquisition stage. | Signal processing NLP Statistical modeling Stochastic methods Data engineering Big data |
| Integrated & Deployable AI Systems | Design AI solutions that meet real operational constraints, from edge computing to robotics. | Embedded AI Edge AI Telecommunications systems Robotics & cobotics Energy efficiency |
What Does AI in Industry Look Like in Practice?
- Mobile Networks & Connectivity : Lower energy consumption, improved performance, and longer equipment lifecycles. AI applied to mobile networks goes beyond optimization—it fundamentally changes how infrastructure is designed, operated, and maintained.
- Predictive Maintenance : An unexpected failure is always more costly than a planned intervention. Our models detect weak signals before breakdowns occur by analyzing sensor data and maintenance histories. The goal is not to replace technicians but to make them more effective.
- Planning & Operations Research : Thousands of field operations to coordinate, regulatory constraints, and resources to allocate. AI doesn’t simplify the problem—it solves it on a scale that no traditional tool can match.
- Time-Series Analysis & Real-Time Decision Support : Some events can be anticipated. Others require immediate action. Our approaches address both challenges through long-term forecasting models and operational decision-support systems designed for time-critical environments.
- Text Data & Knowledge Management : Reports, maintenance records, and technical documentation often remain underutilized within enterprise systems. Natural language processing makes these knowledge assets searchable, structured, and actionable—without exposing them outside your organization.
- Human Factors : System performance depends on more than machines. We develop AI-based approaches for human factors analysis, including cognitive sensing technologies and domain-specific behavioral modeling.
Join Our Ongoing Research Programs
AI for Industrial Efficiency
Leveraging artificial intelligence to improve industrial performance through applications such as corrective and predictive maintenance, technician assistance systems, Spatial AI...
Embedded AI for Autonomous and Mobile Robotics
A collaborative research platform dedicated to intelligent autonomous robotics, covering embedded AI, infrastructure-free navigation, and human-robot collaboration.These technologies are designed to address operational challenges across warehouses, manufacturing facilities, agriculture, and defense environments.
Interested in joining the project or learning more about this research program?
The b<>com Method
From Business Challenge to Production-Ready Solution
Integrating AI into industrial systems requires more than technology. Most projects fail not because of limitations in AI itself, but because the path between business needs and deployed models is poorly structured. Our methodology provides a clear framework.
Requirements Definition & Data Assessment
Business context analysis
Data quality assessment
System constraints evaluation
AI roadmap development
Prototyping & Proof of Concept
Validation using real-world data
Performance metrics definition
Cost estimation
Decision-support analysis
Model Training & Validation
Large-scale model training
Real-world testing
Version control
Model robustness assessment
Integration & Operational Deployment
Integration with existing systems
System compatibility validation
Industrial deployment
Team support and adoption
Scaling AI with MLOps: A Model That Works Today Must Still Work Two Years From Now
Deployment is not the end of the project.
We support production scaling, performance monitoring, and long-term model evolution.
Our MLOps approach ensures that AI systems remain reliable as data sources and operational contexts evolve.
The result is a maintainable, traceable AI system that does not silently degrade when underlying data changes.
What Makes This Approach Different
At b<>com, the same teams work across the entire value chain.
There is no disconnect between the researchers who design solutions and the engineers who deploy them. No loss of knowledge between research and implementation.
As a Technological Research Institute (IRT), we bring research and industrialization together under one roof.
Responsible, Sovereign, and Resource-Efficient AI
Reliability, transparency, and governance are core considerations in every AI project we undertake, supported by dedicated expertise across b<>com.
Your data is hosted within a secure infrastructure governed by confidentiality commitments specific to each collaboration.
Our ambition is to transform the power of AI into real industrial impact through robust, explainable solutions built around efficiency, sovereignty, and operational excellence.
Research and Innovation for Industry
b<>com relies on strong scientific expertise to develop innovative approaches, particularly in advanced statistical learning and generative AI.
Our methodologies are built upon rigorous analysis of your business challenges, available data, and operational objectives.
Research activities are conducted in close collaboration with industry partners to accelerate the transfer of innovation into real-world applications.
FAQ – Artificial Intelligence for Industry
This situation is more common than many organizations expect and is rarely a definitive obstacle.
The initial assessment phase is specifically designed to determine what data can be leveraged and what may still be missing. In many cases, this stage helps clarify the true scope of the project.
We avoid making speculative ROI promises upfront.
Instead, we define measurable business indicators from the beginning of the project—such as avoided failures, reduced intervention costs, or productivity gains—and track them throughout the deployment lifecycle.
The European AI Act, which entered into force in 2024 and becomes fully applicable in August 2026, classifies AI systems according to risk levels.
High-risk systems, particularly in critical industries, healthcare, and infrastructure, are subject to strict requirements, including:
- Training data traceability
- Technical documentation
- Human oversight
- Robustness and compliance testing
At b<>com, AI Act compliance is integrated from the project definition stage through risk assessment, architecture selection, MLOps practices, and technical documentation management.
Our teams continuously monitor the evolution of the European regulatory framework and apply it to collaborative industrial projects.
Industry expertise comes from you. Technical expertise comes from us. That is the principle of co-development—and one of the reasons our projects are successful. Our role is to translate business challenges into solvable technical problems and deliver effective solutions.
Each collaboration is governed by specific contractual commitments. Your data is hosted on b<>com's private infrastructure in Cesson-Sévigné, France, without transit through third-party cloud services and without sharing resources across projects. It remains within b<>com's secure environment and never leaves French territory.
