Legal Twin
An AI-powered workspace that helps lawyers focus on what matters.
Legal Twin is a web-based application designed to support lawyers in managing their daily workload with greater clarity and efficiency. By leveraging AI, the platform automatically summarizes legal matters, highlights key dates and deadlines, and organizes critical information such as involved parties, related documents, and case status — all in one intuitive interface.
The problem
Lawyers often juggle multiple cases, each with complex timelines, documents, and stakeholders. Traditional case management tools are either too rigid or too manual, leading to missed deadlines, fragmented information, and cognitive overload. Legal Twin simplifies this by using AI to surface what matters most — without the noise.
Key challenges
Trustworthy AI Summaries
Designing AI-generated summaries that were both accurate and digestible required careful content hierarchy and trust-building UI elements.
Visualizing Critical Dates
Surfacing hearings, filings, and renewals across cases without overwhelming users or burying context.
Organizing Case Data
Structuring parties, documents, and timelines so they're searchable, filterable, and instantly scannable.
Supporting Diverse Practices
Creating a flexible interface that adapts to varied matter types, from litigation to corporate law.
Design process
- 01
Discovery & Research
Interviewed lawyers across practice areas, mapped the lifecycle of a legal matter, audited existing legal-tech tools, and collaborated with AI engineers to understand model capabilities and limitations.
- 02
Define & Ideate
Built personas like 'The Litigator' and 'The In-House Counsel'. Mapped user journeys from initial access via another legal software through to in-app workflows. Ideated AI summaries, smart date tracking, and contextual document previews.
- 03
Design
Translated ideas into sketches, then low- and mid-fidelity wireframes, then high-fidelity Figma prototypes focused on clarity, trust, and legal precision.
- 04
Test & Iterate
Ran usability testing with legal professionals. Removed visual distractions, made secondary content collapsible, and enhanced the timeline component with meaningful data points so users could quickly grasp upcoming events and case progression.
- 05
Deliver & Collaborate
Provided detailed design specs, joined dailies and sprint reviews, and advocated for continuous feedback loops to improve AI performance post-launch.
What shipped
Transformed Legal Twin into a cleaner, more focused workspace that supports legal professionals in staying organized and efficient, with AI surfacing context rather than adding noise.
- →AI features earn trust through UI affordances — confidence indicators, sourcing, and reversibility matter as much as accuracy.
- →Lawyers want fewer clicks, not more features. Every interaction had to justify itself.