Varick Agents
Varick Agents implements AI inside Fortune 500 companies, designing and deploying AI agents that run real enterprise workflows.
- Role
- Founding Designer
- Timeline
- Spring 2026 – Present

Varick OS
The Operate view, before and after.
Operate is where the engineering team diagnoses a failed run from its trace and gets alerted before the client notices. The first version put the information on screen; the redesign made it legible at a glance: incidents ranked by severity, the run feed and agent health in one frame, and metrics that read as a system rather than a list.
This is just a snippet of my work on the Varick OS. Happy to share more through a call.


Document builder
Client-ready documents, without starting from a blank page.
An internal tool for producing high-stakes, client-ready documents. Writers paste structured content, the builder lays it out in the brand’s system, and the result exports ready to send. It turns repeatable work into a faster, more consistent process without losing craft.
Live at varick-document-builder.vercel.app.

Design system
One source of truth for the brand.
A centralized design system that gives the brand a consistent visual language across the website, marketing, social, presentations and product. It documents the tokens, components and rules the team builds from, so new work is faster to produce and easier to keep on-brand.
Live at varick-design-system.vercel.app.

Brand direction
An editorial photographic language, built in Midjourney.
Enterprise AI brands tend to look like the software: gradients, glowing nodes, stock handshakes. I wanted Varick to look like the companies it works with. So I art-directed a photographic language in Midjourney: film grain, hard afternoon light, limestone and glass, people caught mid-motion.
These are a few frames from that work. They set the tone for the marketing site and sales material, and gave the team a reference for what the brand should feel like before any of it was written down.







Want to learn more?
For a more in-depth case study, please reach out to me at nlrdomin[at]uwaterloo[dot]ca
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