13 video advertisements across 10 brand identities. Every script, video, and voiceover produced through a multi-model AI pipeline — Gemini, Veo 3, and Eleven Labs working in sequence.
The Tempest application needed to showcase its advertising capabilities to potential clients and investors. That meant producing real, varied video advertisements — not mockups, not storyboards — across multiple industries and brand voices. A traditional production approach would require hiring copywriters, videographers, voice actors, and editors for each brand. Multiply that by ten brands and thirteen ads, and you're looking at a production budget that didn't exist.
The work was framed as a proof of concept: could a single person produce broadcast-quality ad content across ten distinct brand identities using only AI tools? Not as a gimmick, but as evidence that a multi-model pipeline could deliver production-ready creative work fast enough and cheap enough to be worth taking seriously.
I designed each brand from scratch — name, visual identity, voice, and positioning — then ran every brand through a repeatable three-stage pipeline. Each stage used a specialized AI model for what it does best, with human creative direction between stages to maintain quality and brand consistency.
Each of the ten placeholder companies received complete brand identity treatment — not just a logo, but a positioning statement, visual language, and voice profile that informed every downstream creative decision. The thirteen advertisements span multiple formats and tones, demonstrating that the pipeline can produce varied output, not just repetitive variations of the same template.
The work was produced as design lead for the Tempest application, in collaboration with a development partner who built the application itself. The ads serve as the product's primary demo content — and the pipeline itself stands as a proof of concept for AI-led ad production: a workflow that can spin up complete brand identities and ship broadcast-grade creative in a fraction of the time and cost a traditional shoot would demand.
Anyone can prompt an AI tool and get a video. The difference is whether you can do it repeatably, across distinct brands, at consistent quality, with a documented process that someone else could follow. That's what separates a demo from a production system.
This project demonstrates the ability to architect a multi-model AI pipeline, maintain brand consistency across varied outputs, and deliver production-ready content without a traditional production budget. The pipeline produced 13 ads across 10 brands. It could produce 130.