Product & UX
Interfaces, flows, and alignment so teams know what they're building and why.
Product · Data · Architecture · AI
I design and build human-centered systems with data and AI.
I'm Daniel, a multidisciplinary designer with roots in architecture and a focus on how people, information, and tools come together. I help teams understand complex problems and shape them into clear, intuitive interfaces — digital and physical. My work ranges from AI tools to product collaboration and environmentally aware projects, all centered on helping people — and the systems they rely on — work better together.
Data & AI
From raw information to tools that answer real questions and support decisions.
Architecture & Space
Systems thinking rooted in how people move, live, and share space.
Overview
What I do now
At RubidiumData, I work at the intersection of product, design, and data. Our team uses AI to automate knowledge-intensive research and development tasks. It's a fast, collaborative environment where ideas move quickly from concept to practical, scalable solutions. My role is to help shape direction, communicate clearly across teams, and design tools that feel intuitive and reliable.
Domains
My work spans three connected areas that share a common thread: helping people understand complexity and act with clarity.
- Product & UX — shaping problems, aligning teams, designing interfaces that support real work.
- Data & AI — structuring information, building flows, and making outcomes easier to interpret.
- Architecture & Space — systems thinking, planning, and understanding human context.
Snapshot
- Based in Berlin
- Active across Europe and Latin America
- Background in architecture; grew into product and data
- Interested in work with social or environmental meaning
- Values clear communication, good collaboration, and thoughtful tools
Featured Portfolio
A selection of projects that represent the range and depth of my work across product, data, and architecture.
Now / Focus
Currently focused on building AI-powered tools that help teams work more effectively with complex information. Exploring how design can make AI systems more transparent, trustworthy, and useful in real-world contexts.