Case Study 01 · SaaS / Legal‑Tech Analytics · 2024–Present

SigmaSight

Defining the information architecture and design system for an AI trial‑risk and negotiation analytics platform — as the company's first product designer.

Role
Principal Product Designer
First design hire · partnered with CEO & CPO
Timeline
Ongoing since 2024
Platform
Web — B2B SaaS
Team
Sole product designer
Presented at the level of process and decisions — no screens or proprietary feature names, per the confidentiality of the domain.
01 — Context
Where the product
stood

An early MVP with real traction — and no design foundation underneath it.

SigmaSight gives insurance defense teams AI‑powered trial‑risk analytics and negotiation tools to counter the data advantage plaintiff attorneys have built over the last decade.

I joined as the company's first product designer, when the platform was an early MVP with no defined information architecture, no design system, and no established interaction patterns beyond what one or two power users had grown used to.

02 — Problem
Inconsistency,
compounding

Every new feature was being bolted on rather than fitting into a structure users could predict.

As the platform added capability, the lack of a coherent IA meant features accumulated instead of composing. There was no shared visual or interaction language for engineering to build against — so inconsistency compounded with every release.

03 — Process
Two audiences,
one architecture

Research with attorneys and adjusters shaped an IA built to serve both.

Working in direct partnership with the CEO and CPO, I set the product vision and strategic design priorities for the platform. I led research with both defense attorneys and claims adjusters — two groups who use the platform differently: attorneys focus on case risk and negotiation posture; adjusters focus on portfolio‑level exposure and workflow efficiency.

Reconciling how those two perspectives needed different views into the same underlying data was the key insight that shaped the information architecture: I defined how case data, risk scoring, and negotiation tools related to each other across the product — structured to serve both audiences instead of favoring one.

In parallel, I built the design system engineering now builds against, establishing consistent patterns for how dense, high‑stakes data gets presented — so new features inherit a coherent visual and interaction language instead of starting from scratch.

04 — Outcome

The foundation the platform has scaled on, release after release.

The IA and design system I established have been the foundation the platform has scaled on through every release since — and remain the standard pattern library the team builds from today.

What Shipped
Information architecture serving two audiencesDesign system engineering builds againstPatterns for dense, high‑stakes dataProduct vision set with CEO & CPO