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Viewpoint eDiscovery

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Overview

 

Viewpoint is a legal and compliance analytics platform used to manage document review for litigation, investigations, and regulatory matters. The product suite includes a modern web-based platform and two legacy on-premise applications: Review and Processing. The long-term goal is to consolidate these tools into a single, browser-based experience under Viewpoint Web.

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As our team prepared to integrate AI-assisted review features into the platform, it became clear that the existing interface and user workflows needed to be re-evaluated. The legacy-inspired design introduced usability barriers and inefficiencies that risked interrupting the experience for current users once the new features were deployed.

 

My focus was on modernizing the UI, improving consistency across the platform, and ensuring that updates could be introduced with minimal disruption to ongoing legal workflows. I began by auditing the existing interface and any prior style documentation. From there, I developed an expanded UI guideline system and created a comprehensive component library to support future development and maintain design consistency. These standards are documented in the LCA UI Guidelines and reflected throughout the new Viewpoint Web experience.

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During my initial audit of the web interface, several usability and design issues emerged that were negatively impacting user efficiency, accessibility, and overall experience. The examples of the old UI below highlight key areas of concern:​

  • Outdated interface design that no longer reflects modern usability standards.

  • Non-compliance with Conduent’s branding guidelines, resulting in inconsistent visual identity.

  • Disorganized navigation and tool structure, making it difficult for users to locate key actions.

  • Over-reliance on right-click actions, hiding essential tools from less experienced users.

  • Accessibility issues, with multiple elements failing to meet WCAG/ADA compliance standards.

  • Inconsistent styling, terminology, and interaction patterns across different screens.

  • Inefficient use of space, leading to visual clutter and reduced clarity.

  • Confusing organization and workflow, creating friction in completing review tasks efficiently.

Actions Taken

 

To address the identified usability and design issues, I led a structured redesign process focused on consistency, accessibility, and efficiency:

  • Conducted comprehensive design audits to identify inconsistencies, accessibility failures, and areas for improvement.

  • Mapped user flows and created wireframes to resolve workflow friction and optimize screen layouts.​

  • Prioritized high-frequency actions by improving visibility and emphasizing them through visual hierarchy.

  • Developed and presented interactive prototypes to product owners, stakeholders, and lead developers for iterative feedback and alignment.

  • Documented all design updates within epics and supporting materials to ensure smooth handoff to development.

  • Performed a post-QA design audit to verify implementation accuracy and maintain design integrity across the final build.

  • Reorganized and simplified navigation and action menus to establish clear hierarchy and reduce cognitive load.

Separation of Actions and Navigation

 

The following example highlights the approach I applied across the product, using this navigation update to illustrate my broader UX work. Through a research-driven, user-centered process, I identified friction points, validated user mental models, and collaborated closely with product, engineering, and stakeholders to translate insights into clear, scalable design solutions that aligned usability, accessibility, and business goals.

 

The existing navigation was problematic because it mixed pages and actions together, forcing users to pause and interpret what would happen before each click. This increased cognitive load, led to misclicks, and slowed common workflows, especially for new or infrequent users.

Updating the navigation was necessary to better align with user expectations: navigation should indicate where you’re going, while actions should clearly show what you can do. Separating these elements improves clarity, reduces friction, and makes the interface easier to scale and maintain.

 

Improving clarity for new users does more than reduce confusion, it has a meaningful impact on retention.When users can move through the product and complete tasks confidently and efficiently, frustration decreases and trust increases. Clear, predictable navigation supports faster onboarding, fewer errors, and a more satisfying experience which are key drivers of long-term user retention.

Research Inputs

  • User interviews

  • Usability testing

  • Click-path analysis

  • Support tickets

  • Stakeholder goals

 

Key Findings

  • Users confuse navigation with actions

  • Tasks are buried among page links

  • Users hesitate before clicking (decision friction)

 
Navigation Separation Framework

  • Side Drawer

    • Primary wayfinding

    • Represents destinations

    • Rarely changes based on context​

  • Top Ribbon​

    • Previous page​

    • Breadcrumbs

Action Separation Framework

  • Top Ribbon

    • Never mixed into navigation

    • Trigger changes, not location

    • Grouped by priority

 

Validation and Iteration

  • Prototype testing

  • First-click testing

  • Task success metrics

 

Outcome

  • Reduced cognitive load

  • Faster task completion

  • Clear separation of intent

  • Fewer navigation errors

Enhanced Review AI Feature

 

As part of the Viewpoint eDiscovery redesign, I contributed to the development of an AI-powered tagging component aimed at improving the speed and accuracy of legal document review. The feature supports reviewers by automatically identifying and suggesting tags based on contextual patterns, key phrases, and case-specific criteria. The goal was to enhance reviewer efficiency, reduce manual tagging errors, and streamline the review process while maintaining transparency and user control over AI-generated suggestions.

Overview

Brief description of the tagging protocol and its purpose within the review process (e.g., relevance, privilege, confidentiality).

 
Dates

Defined time ranges relevant to the case or matter that inform contextual tagging.

 
Keywords and Phrases

Lists of important terms, entities, or language patterns used to train or guide the AI’s tagging logic.

Criteria

Detailed tagging rules or logic statements (e.g., “Documents containing both [keyword A] and [date range B] are flagged for review”).

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Notes

Space for reviewer or administrator commentary, rationale, or clarifications regarding tag behavior and decision-making.

Once AI-assisted tagging is complete, users can search, filter, and organize documents based on the generated Enhanced Review (ER) tags. This functionality allows reviewers to quickly isolate documents by relevance, topic, or other defined criteria, improving efficiency during large-scale investigations and compliance reviews. The filtering system supports both AI-generated and manually applied tags, ensuring transparency and user control throughout the review process.

© 2026 Elisabeth Larkin-Gorman

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