Navigating the AI transition in marketing
IEEE Big Data 2025: the shift from scale to smart
IEEE Big Data 2025 signals a shift to secure, hybrid intelligence. CTO Sabri Skhiri unpacks the engineering reality from the conference: the practical shift to embeddings, the real need for security layers, and the limitations of AI agents in production.
Evaluation of GraphRAG Strategies for Efficient Information Retrieval
Traditional RAG systems struggle to capture relationships and cross-references between different sources unless explicitly mentioned. This challenge is common in real-world scenarios, where information is often distributed and interlinked, making graphs a more effective representation. Our work provides a technical contribution through a comparative evaluation of retrieval strategies within GraphRAG.
Flight Load Factor Predictions based on Analysis of Ticket Prices and other Factors
The ability to forecast traffic and to size the operation accordingly is a determining factor, for airports. However, to realise its full potential, it needs to be considered as part of a holistic approach, closely linked to airport planning and operations. To ensure airport resources are used efficiently, accurate information about passenger numbers and their effects on the operation is essential. Therefore, this study explores machine learning capabilities enabling predictions of aircraft load factors.
Turning retail data into actionable insights
Centralizing data on the Google Cloud Platform (GCP), an international retailer is transforming complex analytics into trusted, production-ready insights—empowering business teams to measure what really matters.
Breaking data barriers
A major automaker pursued a rapid digital overhaul, requiring strong data governance to break silos, ensure GDPR compliance, and enable a scalable data‑mesh foundation.
Beyond the cloud, advanced AI computer vision
From Cloud to Edge: how to transform your business model with Edge AI? Dive into embedded computer vision and edge AI algorithm development with STMicroelectronics STM32 and Euranova.
Unlocking 25 Years of R&D data through graph visualization
A global oil and gas company’s R&D hub amassed decades of complex materials and chemical data, but limited data expertise made it hard for scientists to access, explore, and extract meaningful insights from these siloed datasets
Investigating a Feature Unlearning Bias Mitigation Technique for Cancer-type Bias in AutoPet Dataset
We proposed a feature unlearning technique to reduce cancer-type bias, which improved segmentation accuracy while promoting fairness across sub-groups, even with limited data.
Beyond the hype: how NVIDIA GTC Paris 2025 trends are shaping industry
NVIDIA GTC Paris 2025 revealed an unprecedented scale and breadth of innovation, with a clear focus: not on predicting the future of AI, but on demonstrating how existing technologies are being put to work today. Our CTO Sabri Skhiri was on the ground to bring back insights.
Muppet: A Modular and Constructive Decomposition for Perturbation-based Explanation Methods
The topic of explainable AI has recently received attention driven by a growing awareness of the need for transparent and accountable AI. In this paper, we propose a novel methodology to decompose any state-of-the-art perturbation-based explainability approach into four blocks. In addition, we provide Muppet: an open-source Python library for explainable AI.
Tech insights from GTC Paris 2025
Among the NVIDIA GTC Paris crowd was our CTO Sabri Skhiri, and from quantum computing breakthroughs to the full-stack AI advancements powering industrial digital twins and robotics, there is a lot to share!
AI-assisted coding without process is just chaos
Teams ship AI-generated code faster than ever — and accumulate debt just as fast. The problem isn't the tools. It's the missing process around them.
From data governance to GenAI: strategic insights from Warsaw Tech Summit 2025
This year, one of the biggest technological conferences in Central Europe changed its name to Data & AI Warsaw Tech Summit to reflect the latest technological advancements. Our CTO Sabri Skhiri was on the ground to bring back insights.
S'épanouir dans son travail avec Maryse Colson, Head of people office chez Euranova
Est-ce qu’il est encore possible de rester 10 ans dans la même entreprise en 2025 ? Dans ce nouvel épisode de Métro, Boulot, Finito, j’accueille Maryse Colson, Head of people office chez Euranova, l’entreprise dans laquelle elle évolue depuis 10 ans...
Development & Evaluation of Automated Tumour Monitoring by Image Registration Based on 3D (PET/CT) Images
Tumor tracking in PET/CT is essential for monitoring cancer progression and guiding treatment strategies. Traditionally, nuclear physicians manually track tumors, focusing on the five largest ones (PERCIST criteria), which is both time-consuming and imprecise. Automated tumor tracking can allow matching of the numerous metastatic lesions across scans, enhancing tumor change monitoring.
Efficiency through data governance
A transport company struggled with scattered data and legacy systems, slowing collaboration and critical projects. They needed a centralized platform and operating model to unify governance, improve visibility, and streamline secure, business‑aligned data delivery.
Tech insights from Data & AI Tech Summit Warsaw 2025
11 editions later, one of the biggest technological conferences in Central Europe changed its name to reflect the latest technological advancements. Our CTO, Sabri Skhiri, was present to gather the insights. Here’s a rundown of the key trends, keynotes and talks that took place.
We are a Microsoft Solution Partner for Data & AI
Euranova’s team is thrilled to partner with Microsoft, combining our expertise in data engineering, governance and artificial intelligence with Azure’s advanced technologies to empower our clients.
AI & Knowledge Management, challenge or opportunity?
Together with Fastrack, we invited a community of knowledge management experts to discuss the challenges and opportunities of artificial intelligence in knowledge management. In this article, our Knowledge Manager Charles Bonne dives into the key insights from the discussion.
Unlocking the power of unsupervised learning with interpretable graph embeddings
Unsupervised learning offers immense potential, but deciphering the results is often a challenge. Discover INGENIOUS, a groundbreaking framework from Euranova that generates interpretable graph embeddings that reveal the 'why' behind complex data patterns, empowering organizations to make informed decisions with confidence.
Edge AI engineering: Euranova’s partnership with STMicroelectronics
This partnership focuses on the technical integration of machine learning models into constrained embedded environments. We provide the architectural rigor required to deploy low-latency, high-throughput AI directly onto STMicroelectronics silicon.
Euranova. Implémenter des solutions technologiques qui n’existent pas encore.
Comment savoir quelles technologies utiliser, implémenter, voire créer de toute pièce afin de répondre aux besoins très spécifiques, voire uniques de certaines entreprises?
Flight safety boosted with AI-powered obstacle detection
A leading helicopter manufacturer sought a cost‑effective way to detect thin obstacles during low‑altitude flights, requiring an accurate vision‑based system trained with diverse real and synthetic data to improve safety in challenging environments.