I co-founded Nomiki and serve as CTO. I architected, coded, and deployed the complete platform across Next.js, React, GraphQL, PostgreSQL, Prisma, Docker, and Railway.
The product uses a deterministic multi-model pipeline to manipulate garment images and generate editorials, packshots, colorways, and video content. It powers the official AI image-generation platform used by Castro-Hoodies Group.
Keep the creative rhythm. Reimagine the production.
- 01
Upload
Start with the collection.
- 02
Cast
Choose the models.
- 03
Create
Generate the shoot.
The experience
Begin with the product and the person.
Nomiki follows the familiar rhythm of a photoshoot: upload garments, cast models, and generate images. Collection uploads bring that workflow beyond a single item.
From the product page to the campaign.
The same platform spans clean product imagery, editorial scenes, lookbooks, and motion. The creative context changes while the garment remains the subject.
What holds it together.
Determinism around generative models.
A controlled multi-model pipeline turns variable AI outputs into a dependable production workflow.
A collection is a system.
Bulk workflows connect individual assets to a larger production process.
