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
Sovereign Compute at Scale: Architecting for the Belgian AI Factory Antenna (BE-AIFA)
With the inauguration of the Belgian AI Factory Antenna (BE-AIFA) in mid-2026, the European High-Performance Computing (EuroHPC) landscape has established a localized access framework for…
Pioneering the future of aerial intelligence through advanced 3D digital twins
How do we inspect critical infrastructure safely and efficiently? To tackle this, dive into the combination of aerial platforms with advanced AI to create photorealistic, queryable 3D Digital Twins.
How sales receipt data contributed to review marketing strategy
A sales receipt contain a wealth of primary data on shopping habits, product, and retailer information. Find out how we used this marketing gold mine to support a hyper market in its marketing efforts.
Quantifying Retrieval Quality in GraphRAG: A Schema-Agnostic Approach
In this paper, we propose a novel schema-agnostic framework for the automated generation of synthetic evaluation datasets from KGs. Unlike previous approaches, our framework establishes a rigorous, deterministic ground truth to specifically quantify the retriever performance across nine distinct query categories, including multi-hop and aggregation tasks.
Bridging the Gap: The "Lab-to-Fab" Protocol for Production-Hardened Data Systems
The primary bottleneck in modern data engineering is not a lack of innovative ideas; it is the friction encountered when transitioning a successful prototype into a production-hardened system. When…
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.
Static FAQ replaced by smart chatbot
A Belgian telecom provider wanted to cut support calls by replacing its static FAQ with a scalable RAG‑powered chatbot that delivers accurate, immediate answers through a simple search‑based interface.
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.
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.
Making advertising smarter and more targeted
How AI and data engineering unlock growth for advertisers while improving customer experience.
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!
The LLM coding revolution needs a rulebook
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...
Tot 4 extra landingen per uur dankzij slimme optimalisatie
AI-modellen voorspellen het vliegtuiggedrag en optimaliseren de capaciteit, waardoor een veiligere, nauwkeurigere scheiding en efficiënter beheer van start- en landingsbanen en vluchtpaden mogelijk worden.
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.
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.
Merci d'y avoir pensé !
"L'intelligence artificielle augmente la productivité des entreprises et diminue la pénibilité de certaines tâches. C'est donc clairement une voie de progrès," assure Eric Delacroix, CEO d'Euranova.