Raphaël Caillon

Solace - AI Architect @ Solace

About

My mission is to make AI practical, human, and transformative. From helping manufacturers optimise operations to protecting wildlife and improving healthcare. Technically grounded, creatively driven.

Country

France

City

Greater Paris Metropolitan Region

Industry

Computer Software

Skill

Event Driven, Solace Platform, Machine Learning, Agentic AI, Cybersecurity, Enterprise Architecture, Artificial Intelligence (AI), Sales, SAP BTP, Project Management, SAP HANA, Gestion de projet, First aid, Java, Python, Microsoft PowerPoint, Anglais, Allemand, Intelligence artificielle, Internet des objets

Experience

Solace - AI Architect

Solace

2026-1 - Present · 9 mos

Paris, Île-de-France, France

Building Agentic AI Systems with Solace Agent Mesh

SAP BTP Customer Advisor, AI Lab Manager

SAP

2022-7 - 2025-12 · 3 yrs 6 mos

Brussels, Brussels Region, Belgium

Founder & CEO

Demeter - Work and Wellness

2021-8 - 2022-7 · 1 yr

Versailles, Île-de-France, France

The best workdays, anywhere

UC Berkeley student - IT & Entrepreneurship

University of California, Berkeley

2021-8 - 2021-12 · 5 mos

Berkeley, California, United States

Face-to-face courses : SWE, IT, High tech opportunities, Negotiation, Communication Research in circular RNA structure detection.

Student at Vienna University of Technology - Master's programme Biomedical Engineering

Technische Universität Wien

2021-3 - 2021-8 · 6 mos

Vienna, Austria

Project Engineer | Research & Development

Isep - École d'ingénieurs du numérique

2020-3 - 2021-8 · 1 yr 6 mos

Paris, Île-de-France, France

Project: Segmentation of myelin in Electron Microscopy (EM) Images. Full paper: https://hal.archives-ouvertes.fr/hal-02929744 Dataset : ► 23 EM images provided by the Lariboisière hospital (Paris, 75); ► The associated manual segmentation images into three classes: Axon, Myelin, and Background. The goal of this project is to implement a Deep Learning method, or to improve existing methods, to segment EM images into three classes: Axone, Myelin, Background, help doctors with metrics about these images Main tools and techniques used: ► Python (Keras, Tensorflow) / Matlab ► Images Preprocessing ► Deep Learning ► Transfer Learning (VGG16, ResNet50) ► Data Augmentation ► Test Time Augmentation ► Fine Tuning ► Git

Étudiant

Isep - École d'ingénieurs du numérique

2016-9 - 2021-7 · 4 yrs 11 mos

Paris

Machine Learning Intern

DEEPLINK MEDICAL

2020-8 - 2021-1 · 6 mos

Lyon, Auvergne-Rhône-Alpes, France

The Deeplink Medical's DataLink team hired me on an internship to work on machine learning projects : Our aim is to help radiologists and hospitals best manage consultations and resources with the most appropriate and innovative tools. Our team's current objectives are ambitious; we will be studying patient data, training, and then deploying multiple ML models into the production of Deeplink's ITIS software. I am thrilled to work on a subject that is really beneficial and technically enthralling : Let's get working!

Intern at SAP Presales Garage - Belgium

SAP

2019-9 - 2020-1 · 5 mos

Région de Bruxelles, Belgique

Creating innovating and engaging proof of concepts (both physical as virtual). The goal of this internship is to explore and learn about the newest technologies and to create prototypes that “woooow” SAP's customers.