What exactly do we get?
Working AI agents installed inside your team: design-to-code handoff, design QA, asset production, funnel experiments. They run in your accounts, your people direct them, and everything ships through human review - day and night.
What does it cost?
The audit is a fixed price, told upfront. Implementation is scoped from the audit. The retainer is monthly. Numbers on the first call - they depend on team size, not on how much budget you look like.
Whose accounts and whose IP does this run on?
Yours and yours. Agents live in your workspace, on your billing. Model training on your data: off. The IP language we install has survived enterprise procurement.
Does it ship production code or mockups?
Production code. Agents work from your design system and commit working front-end to your repo - a human reviews before anything merges. Mockups are the input, not the deliverable.
Will this replace my design team?
No. The role changes: your designer becomes the orchestrator of agents - brief in, judgment out. The same output could take half the team; every client so far has chosen the doubling instead. We train your people and sell them on it before anything ships.
Can't we just do this with ChatGPT?
You can, and it will look like it. Hand-prompting in a chat window is like building websites in Adobe Photoshop. What compounds is infrastructure: machine-readable files, design tokens in code, agents that know your design system. That's what we install - and it stays yours.
How do AI agents fit into an existing design team?
They take the production layer, your designers keep authorship. Agents handle handoff specs, resizing, asset production, design QA and design-to-code drafts inside your own Figma, repo and ticket flow - every output passes a human review gate before it ships. Your team stays the same size and roughly doubles what it ships.
Will AI output stay on our design system?
That is the point of infrastructure over tools. Agents read your documented design system and the pipeline includes compliance checks - token usage, component rules, accessibility - before anything reaches review. Figma's own 2026 survey found only 32% of designers trust raw AI output; the review gates are what close that gap.
Who is this for?
Companies with two or more in-house designers and a product that makes money - sports clubs with shops and streaming, banks and payment companies, large e-commerce, media businesses with paid apps. If your design team's backlog grows faster than its headcount, this is the shape of the fix.