IPFC
AI
Desktop
Mobile
Bradning
No-code
UX/UI
IPFC (Intellectual Property for Creators) is the first protection and monetization standard for creative IP in the Generative AI era. Founded by seasoned entrepreneurs, later joined by Brut's co-founder, it lets artists, athletes, and brands register their creative attributes (name, image, voice, style) and control how AI models use them. I joined at the project's inception and designed the product end-to-end: brand identity, wireframes, prototyping, and the final no-code build in Framer, while a four-dev team engineered the API and the multi-agent AI system powering the platform's analysis.
./ Context & Challenge
Generative AI produces over 30 million pieces of content a day , in a single week, 700 million images were generated in Studio Ghibli's style alone, without consent or compensation.
In this new economy, value has shifted from the artwork to the name: an artist's identity, voice, or style is the entry point of every prompt. IPFC set out to regulate usage at that exact moment, before generation even happens.
Our challenge: make an unprecedented legal and technical promise feel credible and understandable for creators who aren't AI experts.
./ Research & Wireframing
We structured the narrative around the product's core loop: register your attributes, monitor their usage across AI models, control violations, monetize through licensing. Low-fidelity wireframes helped us sequence this complex story into a progressive, digestible flow for first-time visitors.
./ Wireframing
Low-fidelity wireframes sequenced the narrative section by section ; problem, paradigm shift, solution, proof. Working at this level of abstraction let us validate the storytelling logic with the founders before any visual investment.
./ The Score Experience
At the heart of the product: users test how exposed their name is. AI agents stress-test major GenAI models; image, text, and audio, and results are rendered as sensitivity scores. The design challenge was making an algorithmic verdict legible and trustworthy: clear gauges, per-model breakdowns, example profiles, and a hierarchy that turns raw AI output into an actionable answer.
./ Prototyping & Iterations
High-fidelity prototypes went through successive versioned rounds (V0 to V0-F), each reviewed against clarity and credibility benchmarks with the founding team. We explored different styles and responsive behavior was designed in parallel, ensuring the experience held on mobile, where most first visits from press and social coverage would land.
./ AI-Assisted Workflow & No-code Build
This project was also an experiment in AI-driven production. We initially attempted a fully AI-generated build, a valuable stress test that revealed its limits in precision and design control. I pivoted to a no-code build in Framer for the production site, keeping AI where it excelled: asset generation, research, and iteration speed.
./ Outcome & Learnings
The platform shipped in about a month with a four-person dev team, laying the foundations for a product later unveiled at the Cannes Film Festival and covered by national press. Le Figaro described IPFC as "the first collective rights-management society of the AI era," alongside features in Les Echos. Key learnings: designing trust around algorithmic verdicts, and knowing exactly where AI accelerates a design workflow, and where human judgment must stay in control.
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