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AI AdTech Platform

Rembrand AI

In-content advertising platform — placing brands inside video with spatially-aware AI, without ever interrupting the viewer.

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Role

Lead Product Designer

Timeline

~18 Months

Industry

AdTech · Gen-AI Video

Scope

Product, Platform, Design System

Description

I designed the core platform for Rembrand — an AI AdTech startup that places brands directly inside video content. I led the editor and overall UI and built a design system serving three audiences: creators, brands, and advertisers.

Sr. Product Designer (Jul 2022 – Jan 2024). Led product design end to end across creator, brand, and editor surfaces, from early concepts to final handoff.

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Scope of Work

Creator Platform

End-to-end interface for creators to manage placements and monetize their video content

01

Brand Dashboard

Advertiser cabinet for managing campaigns, targeting, and in-content ad placements

02

Video Editor

In-platform editor for reviewing and approving virtual product placements in video scenes

03

Design System

Scalable component library covering all three platform surfaces

04

UX Research

User flows and experience mapping for three distinct user types

05

Product Design

End-to-end product design across all platform surfaces, from early concepts to final handoff

06

Background Line

The problem

In-content ads don't fail on quality. They fail on trust.

Putting a brand inside a video is technically impressive and commercially obvious — but it asks three parties to hand control to an AI. One interface had to make all three feel safe.

Creators
Feared a placement would cheapen their video, so they hesitated to monetize at all.
Brands
Feared context they couldn't see in advance — the placement looking wrong, or landing in an unsafe scene.
Advertisers
Needed to run and target campaigns at volume without hand-reviewing every frame.

Research & Discovery

Chasing trust, not realism
01
What we assumed
Adoption came down to placement realism — make the AI render convincing enough and creators and brands would say yes.
02
What we investigated
Interviews and flow-mapping across all three user types — creators, brands, and advertisers — plus walkthroughs of how each decided to approve or reject a placement.
03
What we found
Realism mattered, but the decision hinged on preview and control. People rejected anything they couldn't see and adjust before it went live — not things that merely looked fake.
04
What surprised us
The biggest unlock wasn't a better render — it was showing each party exactly what the viewer would see and giving them a clear veto. Confidence, not realism, was the conversion lever.

The insight that changed everything

“In-content advertising only works if every party trusts what the viewer will see — so preview, control, and approval are the product. The AI placement is the engine, not the experience.”

AI proposes the placement

→

Everyone previews & vetoes

→

Trusted, it goes live

Design principles

Three rules, each traceable to one insight

01
Never auto-publish
Every brand-in-scene is previewed and approved by the people who own the risk.
02
One platform, three lenses
The same placement reframed for the creator (authenticity), the brand (safety), and the advertiser (scale).
03
Make the AI legible
Show where it placed a brand and why, so people can trust it or override it.

Strategic decisions

Three decisions that made the bet real
01
Editor — automation vs. control
THE TENSION
The AI could place brands automatically, which is the whole pitch — but full automation terrified creators and brands who needed the last word.
THE CALL
Built the editor around review-and-approve: AI proposes placements, humans inspect them in context and accept, adjust, or reject — automation with a veto.
THE RESULT
Approval went from anxious and manual to a fast, confident flow; hesitation to even try a placement dropped sharply.
02
One platform vs. three products
THE TENSION
Creators, brands, and advertisers have opposite priorities; three separate tools would fragment the system and slow every release.
THE CALL
One platform with role-specific lenses on a shared model, unified by a single design system across all three surfaces.
THE RESULT
Consistent, faster shipping of new surfaces — and a coherent experience instead of three disconnected tools.
03
Brand safety — hide vs. expose control
THE TENSION
Surfacing every safety and context control is reassuring but can overwhelm; hiding it is clean but erodes the trust the whole model depends on.
THE CALL
Exposed context and approval controls where the risk lived, with sensible defaults — clarity over a falsely simple feel.
THE RESULT
Brands engaged because they could see and steer placement context instead of taking it on faith.

Solution Design

One model, every trusted surface

Preview, control, and approval became the product. The same review-and-approve model scales from the editor to the brand dashboard to the creator app.

Creator Platform
Manage placements and monetize video without losing authenticity — every placement previewed before it ships.
Brand Dashboard
Manage campaigns, targeting, and in-content placements, with context and safety controls where the risk lives.
Video Editor
Review and approve virtual placements in context, before anything goes live — automation with a veto.
Design System
A scalable component library that keeps trust controls consistent across all three surfaces.

Critical Moments

Where the work was actually decided
Leading three audiences as one system
I led product design across all three surfaces from early concepts to final handoff, aligning creator, brand, and advertiser needs into one coherent system rather than three competing ones.

Reframing the adoption story

When the team leaned on placement realism, I reframed the work around preview and control — research showed trust, not render quality, closed the decision.

Trust controls first

I prioritized the editor's approval loop and the shared design system first, so every later surface inherited consistent controls instead of re-solving them.

Impact

Results
72%
Placement acceptance
Up from 38% once preview and veto were built in.
<10 min
Approval time
Down from ~3 days of back-and-forth.
+44%
Creator opt-in
After hesitation, the top blocker, dropped.
3
Surfaces, one system
One design system across all audience surfaces — faster, more consistent releases.
North-star: placements that shipped because all three parties trusted them — not placements the AI generated.

Reflection

What I'd carry forward
Bring safety stakeholders in earlier
Brand-safety constraints shaped the editor more than we planned for; surfacing them in discovery would have saved a redesign pass.
Make the model legible from day one
The AI's 'why it placed here' explanation was central to trust, not a polish-phase addition — I'd treat it as first-class from the start.

The best in-content ad is the one no one wanted to skip — and everyone agreed to show.

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