Data Strategy and Consulting

  • Data strategy definition: new business model, connected plants / products, data/AI to better know your customers and/or optimise your operations & processes
  • Data/ AI use cases generation and qualification driven by business value

Industry 4.0

  • Industrial data model definition to enable Industry 4.0 use cases
  • Statistical process control (control charts, six-sigma, key process parameters)
  • Quality control (scrap avoidance) and predictive maintenance (OEE)

Machine Learning / AI

  • Data acquisition & fusion from multiple sources (sensors, measurement tools such as laser tracker, 3D scan…)
  • Data processing, visualization and alerting
  • State-of-the-art models: ML for prediction or classification, pose estimation (computer vision)

Systems Modelling

  • Operational Research and optimization
  • Mathematical & physical models to enable digital twin use cases
  • Software / hardware design

Databold SAS

Who are we ?

We are an international team of passionate and experienced Digital Transformation professionals from data and industrial operations backgrounds.
Powered by state-of-the-art technologies and agile project management methods, we help mid-cap companies unlock the full potential of their data through a rapid and bold deployment experience.


Hadi Mahihenni
Hadi Mahihenni -
Co-Founder & CEO

Hadi graduated from Ecole des Mines de Paris (2008) and Ecole Polytechnique de Montréal. He has been since working in various industries (eg. process industries at Air Liquide and Lafarge) and sectors (from construction materials to aerospace). He has also been advising large industrial clients on their data transformation (ex-Director at Capgemini Invent) and how to develop and scale their business use cases leveraging data and AI. His main focus is on Digital Manufacturing (predictive maintenance, predictive quality, energy analytics, AI for logistics, ..) with more than 50+ use cases track records.

Key expertise
  • Data/AI transformation strategy & implementation at scale
  • Data x AI x Operations use cases (eg. digital twin, predictive maintenance, quality, supply chain, process mining ..etc.)
  • New business models via tech/data innovation
  • Agile product/project management
  • Lean Manufacturing, 6 sigma, SPC
Guillaume Bonhomme
Guillaume Bonhomme -
Co-Founder & CTO

Guillaume graduated from Ecole Polytechnique (X) and Ecole des Mines de Paris (2013). He worked in various industries (eg. aerospace, real estate, public transportation) as a Strategy Consultant and Data Science director. He successfully implemented data-driven use cases (predictive pricing, natural language processing, advanced data cleaning, data visualisation & analytics) in different contexts (eg. manufacturing, procurement, web & software development) and is used to working with various team size and tool set. His main focus is on using Data Science & AI to build practical solutions and unlock business & operational value.

Key expertise
  • Data science and AI
  • Mathematical & systems modelling
  • Agile product/project management
  • Digital transformation
  • Operational excellence