Laura Martel
AI for R&D, engineering and quality teams
I cut weeks off literature and standards review, technical reporting, and the decades of documents nobody can search — with tools built by someone who has done the science herself. PhD in materials chemistry, former research scientist at the European Commission's JRC. I started in chemistry, materials and nuclear; the workflows are the same anywhere an answer has to hold up to scrutiny.
What I do for technical organizations
AI Opportunity Audit
A short, fixed-scope assessment of how your team actually works — literature and standards review, reporting, experimental and production data, legacy archives — that identifies where generative AI saves real hours, and delivers a prioritized roadmap with effort and risk estimates. You see the value before committing to a build.
Discuss this →Technical Documents & Legacy Archives
The problem nearly every technical organization has: decades of test reports, specifications, lab notebooks, quality files and scanned PDFs that nobody can search. I build extraction and retrieval pipelines that make them answerable — sources cited on every answer, so an engineer can verify the claim instead of trusting it. EU-hosted or fully on-premise where confidentiality requires it.
Discuss this →AI Training for Technical Teams
Hands-on workshops that get engineers, researchers and quality staff productive in days: writing effective prompts for technical work, checking model output against domain knowledge, and knowing when a model should be trusted — and when it shouldn't.
Discuss this →Sectors I work in
- Chemicals & process industry
- Pharmaceuticals & life sciences
- Food & agri-processing
- Mechanical engineering & automotive
- Materials & metallurgy
- Nuclear & other regulated environments
I started in nuclear materials research, inside one of the most tightly regulated research environments in Europe. A workflow that survives an audit there will survive one in your quality lab.
Why technical teams talk to me
PhD in materials chemistry (Université d'Orléans) — I've run the experiments, written the papers, and lived the workflows I now automate.
Research scientist at the European Commission's Joint Research Centre (Karlsruhe), working on nuclear materials in one of Europe's most regulated research environments.
Peer-reviewed publications in materials chemistry and nuclear science — see them on Google Scholar.
AI R&D engineer at imki (Strasbourg), building generative-AI products in production — including work on the European PERCEIVE research project.
How I work
Start small. Every engagement begins with a scoped assessment, so you know the value before committing to a build.
Your data stays yours. I work with EU-hosted and self-hosted models where confidentiality requires it, and put data-handling rules in writing.
Scientists in the loop. I build tools your researchers can verify, challenge, and correct — because in this sector, an unverifiable answer is a useless answer.
Professional Background
From the lab bench at the JRC to production AI systems in industry.
- AI R&D Engineer – imki (Strasbourg, France)
- Research Scientist – European Commission JRC (Karlsruhe, Germany)
- PhD in Material Chemistry – Université d'Orléans, France
Beyond client work, I co-organize Stras-IA, a series of AI events in Strasbourg.
Let's talk about your workflows
A short message about how your team handles documents, reporting or experimental data is enough to find out whether AI can save real time — and where to start. Reach me on LinkedIn, or reveal my email address below. No slides, no obligation.