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CASE STUDY -> SYSTEM DESIGN

CASE STUDY -> SYSTEM DESIGN

CASE STUDY

Contracts weren’t broken.
The way we structured them was.

From storage hierarchy → relationship-driven system.

ROLE

Product Designer

CONTEXT

Enterprise CLM platform

FOCUS

System design, AI enablement

YEAR

2026

The problem wasn’t complexity.
It was that the system was lying

It showed structure as folders.
But contracts don’t work like folder - Contracts have historically been treated as static files stored in folders. This "flat" storage model fails to represent how legal obligations actually function: as a living, interconnected web where one document can modify, terminate, or extend another.

THE CHALLENGE
“At first, this looked like a search problem.

So we tried everything -> filters, OCR, indexing.
Nothing worked. Because users weren’t searching. They were reconstructing meaning

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Contracts as Folders

In the existing system, users navigated through a nested directory of PDF files. To understand the current state of an agreement, a lawyer had to manually open 5-10 different files and mentally reconcile the changes.

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"The core problem wasn't a lack of search or better OCR, it was the fundamental absence of a structural data model that mirrors legal intent."

The Decision Moment

We faced a choice: optimize the current folder-based browsing experience, or rebuild the data architecture from the ground up to treat contracts as a system. We chose the latter, knowing it would be a harder technical lift but would eventually become the bedrock for AI-driven intelligence.

THE CONCEPTUAL SHIFT

From storing contracts →
to representing relationships

A contract isn't a file. It is a system composed of Authority (the Master Agreement), Relationships (SOWs and Amendments), and Evolution (Time and Status).

Authority
Identifying which document holds the final "source of truth" in a chain of amendments.
Relationships
Mapping how an NDA impacts a Master Service Agreement across global entities.
Evolution
Visualizing the life-cycle of terms as they are negotiated and modified over time.
Structure

Defines the hierarchy of authority. Every document knows its 'parent' and its scope of influence.

Relationships

The connecting lines that show hierarchy and precedence across the entire portfolio.

Documents

The physical evidence. The file becomes an attribute of the relationship, not the container of it.

A Clearer View

Visible Relationships

Instead of digging through PDF pages, legal counsel can now see a tree of influence. Which amendment changed the liability cap? It's now a primary visual signal.

Authority Clarity

The system highlights the "Active Clause" automatically, suppressing deprecated terms from the primary view while maintaining an audit-ready history.

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Refining the Micro-interactions

Translating the broad architectural vision into functional UI components that respect the speed of legal review.

Contextual Search

Search results now return "Entities" and "Relationships" rather than just text matches. "Show me all active MSAs with 30-day net terms" becomes an instant query.

Hierarchy Visibility

A sidebar navigation system that is purely system-driven, showing the logical structure of a legal parent-child relationship across multiple years and entities.

AI Rediness

"You can’t layer AI on top of a broken structure. Structure defines what AI can understand."

By providing a structured data model, we eliminated the hallucinations common when LLMs try to parse flat folders. The AI now has a 'map' to follow, ensuring it pulls data from the correct, most recent version of a legal clause.

-40%

REVIEW TIME

Efficiency gained by removing hierarchy reconstruction tasks.

100%

DATA INTEGRITY

Elimination of conflicting "current" versions in the system.

85%

AI ACCURACY

Context-aware extraction with minimal human correction.

Structure enables understanding.
Understanding enables intelligence.

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