About Mattis
- Complete SaaS Products — architecture, development, deployment. Next.js, TypeScript, Supabase/Postgres, Stripe Connect.
- Applied AI Integration — conversational agents, document extraction and structuring via LLMs, business process automation. Not demos: production systems.
- Automation & Scraping — data pipelines, asynchronous jobs (BullMQ), Playwright, API integrations.
- Deployment & Reliability — Vercel, AWS, Docker, monitoring (Sentry). What I build, I make it run.
French
Native or bilingual
English
Fluent
Experience
- AstelaFounder & Full-Stack DeveloperSOFTWARE PUBLISHINGMarch 2025 - Today (1 year and 5 months)Aix-les-Bains, FranceFounder of Astela, a SaaS management platform for small French retailers (grocers, bakers, tobacconists, specialty shops): online store creation, invoicing, order management, and integrated AI agent.Product designed, developed, and operated entirely by myself, now in production with paying clients.Development— Next.js, TypeScript, Supabase / PostgreSQL, Drizzle ORM, Stripe Connect for merchant payments. Monorepo architecture, asynchronous jobs (BullMQ), catalog scraping and enrichment (Playwright).Applied AI— design and production deployment of Mael, a conversational agent that assists merchants daily. LLM integration for real business use cases, not just demonstrations.Infrastructure & Operations— Vercel, AWS, Docker, monitoring and alerting (Sentry), partner data integration pipelines (SFTP, catalog synchronization).Beyond the Technical— company legal structuring, negotiation of distribution partnerships, customer relationship management. I understand the business cost of an architectural decision because it's mine.
- YXIR EDFFull-Stack & Infrastructure DeveloperSOFTWARE PUBLISHINGApril 2023 - December 2024 (1 year and 8 months)Paris, FranceDevelopment of an anomaly detection and matching application, from the interface to model deployment.
- Anomaly management application — creation, qualification, and tracking of customer anomalies. Next.js / TypeScript front-end, Django back-end. Volume up to one million anomalies for the largest accounts.
- Embedding similarity engine — automatic matching of similar anomalies on a scale of millions, avoiding duplicate processing and leveraging past resolutions.
- LLM model deployment on EC2 Inferentia — production inference on dedicated AWS silicon, for high availability and reduced cost per query compared to traditional GPU infrastructure.
- Multi-environment AWS Fargate infrastructure — containerized architecture, automatic scaling, isolated dev/staging/prod environments.
- VincturaCTO - Co-founderHEALTH AND WELLNESSOctober 2020 - November 2021 (1 year and 1 month)Paris, FranceCo-founder and technical lead of Vinctura, a platform for processing health data from connected devices: patient monitoring, diagnostic assistance, and structured data provision for medical research.I led the entire technical design of the product: platform architecture, ingestion pipelines for data streams from connected devices, structuring and normalization of heterogeneous medical data, and compliance with specific health data constraints (GDPR, sensitive data hosting).A technically and regulatorily demanding project, which taught me to build a product in an environment where data reliability and traceability are non-negotiable.
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Education
- Baccalauréat S (French scientific baccalaureate)Lycée Saint Ambroise2018Baccalauréat S