About Simon
- Identify AI use cases with high ROI and eliminate projects without value
- Frame realistic and prioritized data/AI projects
- Manage end-to-end delivery (business, tech, data)
- Industrialize MVPs into robust and scalable solutions
- Monitor real-world performance: models, usage, business impact
- Risk prediction models (fire, industrial) used in production
- AI/IoT SaaS platform deployed in complex environments
- Structuring and leveraging +80 data sources (IoT, geospatial, business systems)
- Process automation via NLP, computer vision, and AI agents
- Production deployment of critical solutions (industry, insurance, public sector)
- an AI project is unclear, poorly framed, or lacks clear ROI
- a POC needs to go into production but is blocked
- business and technical teams are not aligned
- complex data needs to be leveraged quickly
French
Native or bilingual
English
Conversational
Experience
- Weewio SAS🏗️ President & Technical DirectorTECHJanuary 2018 - January 2026 (8 years)Strasbourg, FranceCreation and leadership of Weewio, a deeptech startup developing a SaaS platform combining AI, IoT, and geospatial data for industrial and environmental risk management.👉 Objective: transform complex data (IoT, field, open data, industrial systems) into high-impact operational decisions (risk reduction, performance improvement).🚀 AI & Product Management
- Framing and defining AI use cases with high ROI: risk prediction, fire detection, site scoring
- Design of ML, NLP, and computer vision models
- Structuring multi-source data pipelines (80+ sources: IoT, geospatial, public data, client systems)
- SaaS architecture choices: cloud/on-premise, APIs, microservices, LLMs
⚙️ Delivery & Industrialization- Development and production deployment of MVPs (full product cycle)
- Industrialization of AI solutions (CI/CD, Docker, monitoring)
- Model performance monitoring (accuracy, drift, business ROI)
- Deployment in critical environments (industry, insurance, public sector)
👥 Management & Coordination- Management of a team of 10+ people (data, dev, UX, business)
- Multi-stakeholder coordination (clients, partners, technical teams)
- Agile organization (Scrum: backlog, sprints, prioritization)
- Direct interface with decision-makers and business management
🔥 Key Achievements- Fire risk prediction model based on field and scientific data
- Digital twins of industrial sites (dynamic risk mapping)
- NLP system for extracting and structuring heterogeneous data
- Process automation via computer vision and AI agents
- Platform used for multi-site industrial risk analysis
💡 PositioningComplete CEO/CTO experience focused on product and impact:👉 from strategic framing to production deployment👉 from business need to operational solution👉 with an obsession for ROI and real-world usage
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Education
- Engineering DegreeInstitut National des Sciences Appliquées (INSA)Titre d'ingénieur, Grande école d'ingénieurs, Spécialisation Mécatronique (Mécanique, Electronique, Programmation, Robotique)
- University Diploma for Student EntrepreneursUniversity of Strasbourg, Faculty of Economics and Management