Case Study — Enterprise AI Platform
I was SAIC's first UX hire. No design function, no system, no process. I built the design language for an AI platform used across the Department of Defense — from a blank Figma file.
The Problem
SAIC's Innovation Factory had built powerful AI capabilities — NLP pipelines, computer vision models, data fusion tools — that almost nobody outside the data science team could actually use. The technology existed. The gap was translation.
When I joined in 2021, there was no design function, no design system, no component library, no process, and no documentation. The team was shipping AI-powered tools directly to DOD operators and analysts who weren't data scientists — and the gap between what the technology could do and what users could accomplish with it was enormous.
"The technology existed. The gap was human translation.""
The Audience Problem
Tenjin served two fundamentally different user types with different mental models, different vocabularies, and different relationships to the underlying technology. Understanding and then designing a single platform that served both without alienating either was the central UX challenge.
Only once I understood both of them completely — their vocabulary, their mental models, their relationship to the technology — could I design an interface that didn't make either one feel like a second-class user. That's not a UX insight. That's just the work.
The Foundational Decision
Before designing a single product screen, I made a decision that shaped everything that followed: I would not design individual features. I would design the system that generated features.
The Innovation Factory was running multiple parallel programs — Tenjin, Advana, CDM — each with different product teams and engineering leads. Without a shared design foundation, each program would drift visually and behaviorally, creating a fragmented experience across tools that were supposed to feel like a unified platform.
I led a team of designers and engineers that built a Figma-based design system from scratch: component library, typography scale, color system, spacing tokens, usage documentation, and a Storybook integration, giving engineers living reference for every component. This wasn't a UI kit — it was the shared language that let a 250+ person team ship consistently at scale without requiring a designer in every room.
"I didn't just design features. I designed the system that generated them."
Key Screen — Entry Point
Key Screen — Most Important
Key Screen — AI Pipeline
The Full Surface
Admin Dashboard
Tool management for program administrators — toggle integrations like Koverse, Databricks, and Tableau on or off, add custom tools, and manage user access via Keycloak. The same design language scales from analyst-facing workflows to admin-facing controls.
Datasets
A searchable, tag-filtered library of datasets available across the platform. Filter chips (My Datasets, News, Models) reduce scope without hiding breadth. The grid layout treats data assets the same way the Accelerator Store treats AI capabilities — browsable, labeled, and ready to act on.
What the Design System Enabled
By the time Tenjin was deployed across programs, the design system had become the connective tissue for the entire Innovation Factory's product surface.
Takeaways