• Graph Data Science Consulting

    We help companies turn multi-dimensional data
    into actionable insights through graph analytics and
    graph visualizations.

Services & Expertise


Orbifold B.V.
Leuven, Belgium.

Phone: +32-498-103288
Email: info@orbifold.net
Twitter: @theorbifold

Orbifold Consulting specializes in articulating graphs as a tool to extract business insights from data. Operating as an independent consulting company for more than 20 years, we combine business expertise and scientific know-how in bespoke software solutions. We deliver unique and innovative solutions using state-of-the-art tools and technologies.

We count amongst our customers world-renowned enterprises across all industries. Graph techniques can be applied to almost any business domains but are particularly well suited to fraud analysis, marketing optimization, operational intelligence, anti-terrorism, forensics and any form of large-scale knowledge management. Our expertise in these domains is broad and deep; from PhD-level scientific research to sophisticated JavaScript front-end development, from advanced graph machine learning techniques to cloud devops, from management consulting to startup boosting.

Being vendor neutral enables us to put together the best technology for every project, we’re innovation partners from ideation to implementation.

yFiles v2.4 by @yworks is out and boasts massive visualizations into the millions using WebGL. Improved developer experience and automatic layout makes it an exciting new release and a great foundation for all your graph visualization needs. https://t.co/IaH2Tgm80J #diagramming https://t.co/yOcRFg72nA
Thanks to WebAssemblies you can run JupyterLab in your browser. Absolutely awesome, the never-ending ascent of browsers and #JavaScript. #JupyterLite

https://t.co/omiYB1fxrr https://t.co/kzihMMZSem
That is one awesome graph visualization 🥰 #dataviz https://t.co/lTGMDGNJHt
Stunning graph layout performance from Ogma by @Linkurious: 31K nodes and 40K edges in around a minute. Not even WebGL and still fully interactive. https://t.co/wp8EM88dxw
Announcing the official Neo4j GraphQL Library. @neo4j https://t.co/nDLAQDoRO8 https://t.co/qDmFYQxOw9
Kudos to @theaisummer for the excellent into on how Graph Neural Networks (GNN) work. An introduction to graph convolutions from scratch. https://t.co/4HVm7WY8BX #GraphMachineLearning https://t.co/viUlUA02Az
Why has nobody integrated graph embedding algorithms into graph visualization yet? JavaScript Node2Vec or GNN predictions realtime while creating diagrams. Automatic labeling while drawing. Anyone? #GraphRepresentationLearning #Diagramming
Spektral is a Python library for graph deep learning, based on Keras and #TensorFlow. The main goal of this project is to provide a simple but flexible framework for creating #GraphNeuralNetworks. https://t.co/xjynmhUrgE #KnowledgeGraphs https://t.co/0xmpVyOIPG