Built to shipand built to last
Commissioned web work for people whose name is the business: brand identity through to a running site with a CMS, a blog and a newsletter behind it, owned by the client afterwards. And my own mobile apps — fitness, finance, nutrition — built with Flutter and Firebase. Different stacks, one standard: shipped, hardened, and handed over in a state someone else can maintain.
- Client site, end to end
- 01
- Shipped apps
- 04
- Downloads
- 100k+
Client websites,
end to end
Consultants, coaches, advisors — one person whose reputation is the product. I design and build the whole thing: identity and logo through to a running site with a CMS, a blog and a newsletter behind it, handed over so you can keep changing it without me.
Brand & corporate design
Logo, palette, type and motion — the identity before the site.
A site you own
Pages, blog and newsletter in a CMS with your name on it.
Guardrails, not handcuffs
Security, speed and correctness, checked automatically.
Handover that survives me
A codebase where you can change copy and colour without me.
In practice
von Wartenberg Leadership
The complete web presence for Dr. Peter von Wartenberg, who advises executives and organisations on leadership. Brand first: the “Rising Arcs” mark and the claim “Learn to Serve & Protect”, then a bilingual site built to carry them — Next.js and Tailwind, Payload as the CMS on Neon Postgres, Brevo behind the newsletter, Vercel for delivery. Pages, blog and mailing list belong to the client, and the release pipeline keeps a cosmetic change from breaking anything underneath it.
Scope
- Brand identity
- Logo — the “Rising Arcs” mark
- Corporate design
- Motion & animation
- Animated logo & level states
- Web design
- Payload CMS setup
- Newsletter & blog
- Bilingual DE / EN
- CI/CD and guardrails
Stack
- Next.js
- Tailwind CSS
- Payload CMS
- Neon Postgres
- Brevo
- Vercel
- TypeScript
Models don't create value in notebooks — they create it in production. I build the MLOps and AI Services platforms that take machine learning from experiment to reliable, governed, at-scale systems.
- 01ML platform architecture
the training, deployment and monitoring path a team uses daily, not a single pipeline that works once
- 02Prototype to production
taking a model that runs on a laptop and making it something an on-call engineer can be woken up for
- 03AI features inside a product that already exists, scoped so the useful part ships before the budget is gone
- 04Direction for a team already building it
architecture, tooling, and the handful of decisions that are expensive to reverse
Projects
Also shipped
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