Conversation Design for AI-driven Benefits Verification

Built a visual conversation builder for Infinitus's AI-driven insurance verification system, enabling faster automation of complex workflows through reusable dialogue components.

Background

Infinitus faced a critical challenge while scaling their benefits verification automation.

While their AI system could handle basic calls, complex workflows required significant human operator intervention.

In order to build and debug these complex conversations at scale, conversation designers needed to make and manage flows.

The existing tool was becoming a bottleneck — conversation designers struggled with an unintuitive interface, lacked visual feedback, and could not easily reuse components across different flows and customers.

Key challenges

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    Conversation designers struggled with unintuitive interface
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    Lacked visual feedback
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    Could not easily reuse components across flows and customers
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    Complex workflows required significant human operator intervention

Outcomes

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    Led design and engineering to overhaul the conversation builder tool, enabling users to convert new SOPs into automated dialogues >30% faster
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    Enabled conversation designers to flatten conversations, opening the door for more sophisticated automation
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    Improved response time to client requests by >20%
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    Standardized component implementation, including providing automatic usage metrics for product and engineering
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    Enabled rapid iteration on conversation designs through improved visual feedback and reduced QA time by >20%

Business Impact

Improved Efficiency
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    Reduced time to create new conversation flows
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    Decreased maintenance overhead for existing flows
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    Enabled rapid testing of automation strategies
Better Scalability
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    Standardized components reduced implementation time
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    Reusable patterns accelerated new development
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    Improved visibility into system behavior
Enhanced Quality
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    Real-time preview caught issues earlier
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    Standardized validation improved data quality
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    Better visualization reduced implementation errors

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Solution

Redesigned the conversation builder from the ground up, focusing on three key innovations

Visual Flow Editor

Improved visualization and editing of conversation flows

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    Created intuitive visual interface for designing complex insurance verification dialogues
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    Visually map and modify conversation flows
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    Preview utterances and responses in real-time
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    Reuse common dialogue patterns across different insurance providers
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    Validate outputs against known data formats
Standardized Component Library

Increased consistency and reusability of dialogue components

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    Developed comprehensive set of reusable dialogue components
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    Enforced consistent implementation patterns
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    Provided automatic usage metrics
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    Simplified complex interaction patterns into reusable blocks
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    Enabled rapid prototyping of new conversation flows
Output Management System

Improved data quality and system integration

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    Built flexible system for managing conversation outputs
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    Enforced data validation rules at design time
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    Provided clear visibility into data dependencies
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    Enabled cross-organization output standardization
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    Simplified integration with downstream systems

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Process

User Research
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    Conducted extensive shadowing sessions with operators and conversation designers
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    Interviewed >20 users across different roles to understand pain points
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    Created detailed workflow maps to identify optimization opportunities
Iterative Design
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    Developed multiple design iterations with stakeholder feedback
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    Built high-fidelity prototypes for user testing
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    Conducted usability studies to validate design decisions
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    Iterated based on quantitative usage data
Implementation Strategy
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    Created phased rollout plan to minimize disruption
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    Built adapter layer to support gradual migration
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    Developed comprehensive documentation and training materials
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    Established new design patterns for future automation tools