AI Call Explorer
Reimagining how benefit specialists analyze thousands of customer service calls using AI-powered search, summaries, and insights.
Role
UX Lead • Information Architecture • Visual Design • Content Strategy
Timeline
3 months
Team
Product Lead
Data Scientists
Developers
Business Stakeholders
Responsibilities
• Discovery
• UX Research
• Product Strategy
• IA
• UX Design
• Prototyping
• AI Experience Design
• Design System
Our Approach
We partnered with business stakeholders, data scientists, and developers to evaluate the existing MVP, identify workflow gaps, and define a scalable product vision focused on AI-assisted call analysis.
Responsibilities
Stakeholder Interviews
Product Discovery
Workflow Analysis
IA
UX Strategy
Wireframes
High Fidelity Designs
Future Vision Roadmap
Problem
The existing MVP allowed users to search calls using multiple disconnected filters and manually review transcripts one call at a time.
Pain points
• Too many search fields
• Difficult to locate relevant calls
• No meaningful summaries
• Required opening individual calls manually
• No AI assistance
• Limited operational insights
Discovery
Users searched using numerous independent fields.
Once results appeared, they had to manually enter Contact IDs to review calls.
The workflow required unnecessary context switching.
Opportunity Areas
We identified four major opportunities
Simplify Search
Improve Navigation
Surface Insights
Introduce AI Assistance
Landing Page Redesign
Explored multiple layouts for balancing search, analytics, recent searches, AI, while minimizing visual complexity.
Final Vision
The final concept unified Search, AI, Summaries, Insights Call Results into a single workflow that reduced unnecessary navigation while supporting both specialists and managers.
What I Learned
Designing AI experiences required balancing transparency, automation, and user control. Rather than replacing analysts, the goal became helping them reach better decisions faster through summarized information and conversational search.