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Learnings from paying artists royalties for AI-generated art

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A retrospective on Tess.Design, our attempt to make an ethical, artist-friendly AI marketplace. We launched Tess in May 2024 and shut it down in January 2026.

In 2024, we launched Tess.Design, a marketplace of fine-tuned AI image models where artists got paid a 50% royalty every time someone used their style. Less than two years later, we shut it down. This post is a candid account of what we built, what the data showed, and what any entrepreneur should know before trying to build an AI licensing business on top of creative talent.

The Problem We Were Solving

By 2023, AI image generation had become mainstream and deeply controversial. Image generation models like DALL-E and Midjourney trained on billions of scraped images, often without artist consent or compensation. Surveys consistently showed that consumers believed artists deserved payment when AI generated content in their style. Yet no business model existed to make that happen.

Media companies were in a stalemate. Outlets like Rolling Stones and Fortune wanted AI-generated imagery for blogs, thumbnails, websites, and graphics. But their legal teams were nervous about copyright exposure, given the numerous ongoing lawsuits. So the publishers either banned AI tools entirely or turned a blind eye to their use, hoping for the best.

Tess was our answer to this problem : an AI image generation platform where every image was traceable to a single consenting artist, who earned a royalty in its production. In this way, we argued that Tess was the first “properly-licensed” image generator that produced the same quality images as Midjourney and other leading models.

How the Business Model Worked

Tess Artists submitted a set of their work to fine-tune a Stable Diffusion base model. The resulting model, linked to that artist's aesthetic, was listed on a public marketplace at tess.design/models. Subscribers paid for access; the artist earned 50% of the revenue when subscribers used their model.

The legal architecture mattered as much as the product. Working with Fenwick, we constructed a contributor agreement and Enterprise Service Agreement built on a novel copyright argument. We posited that because all outputs were stylistically transformed into the contributing artist's aesthetic, the artist held copyright over the derivative works and could license them downstream to customers. This created a clean chain of copyright ownership, something no other AI image generator at the time offered.

To seed the marketplace, we offered 25 founding artists an advance royalty of $300–$4,000 based on their portfolio quality and audience reach. In addition to income, we pitched artists on these value propositions:

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