Industry
Medical, Insurance
Company
Optum
Category
AI Assistant, Conversational UI
The Challenge
Taking a step towards shaping the next generation of enterprise healthcare conversational AI frameworks and craft an intuitive, seamless, and compliant assistant experience for our users.
How we elevated self-service adoption and optimized conversational data.
The short story: I designed the prompt frameworks, constrained UI patterns, and error-recovery loops that made the data clean enough for the model to succeed.
Tailoring the Entry Point to Prevent Cognitive Overload
An intent-based entry point dynamically tailors the greeting to a user's live account status. As soon as a user starts typing, the interface deploys progressive disclosure to shift visual focus, eliminating distractions and keeping the user entirely centered on their query.
Streamlining Care Scheduling
Designed a mixed-mode conversational flow connecting open-ended chat to adaptive UI shortcuts. By instantly extracting intent and account history, the system eliminates search friction for an immediate self-service path or a seamless agent handoff.
Rigid Forms to Contextual Feeds
Embedded multi-select filters and location pickers directly into the chat stream to capture complex patient data without drop-off. By naturally gathering clinic and provider preferences in-line, the system builds an agent-ready payload without forcing users through a clunky form.
Agent Handoff & Session Continuity
When a user explicitly chooses to switch to a live agent, the interface passes them over while retaining their chat thread history. To mitigate frustration and drop off during the transfer, the UI displays clear, real-time wait times the moment they choose to connect. Additionally, if a user tries to close the window during an active chat, a quick warning pop-up prevents them from losing their live chat session unintentionally.
Bypassing Complex Portal Workflows
Users frequently turn to a chat assistant when they are frustrated by confusing, multi-page portals. By surfacing live booking details directly inside the feed, the assistant cuts through deep navigation paths to process cancellations in real time—eliminating the friction of a context switch.
Translating Clinical Data into Actionable Insights
Medical jargon and lab results can be difficult for patients to interpret without context. The assistant simplifies complex health data by delivering plain-language breakdowns within the message stream. When an inquiry requires deeper record navigation, the interface surfaces structured shortcuts to specific platform areas like test histories and care pathways—bridging open-ended questions with definitive patient data.
Intercepting Sensitive Data In-Flight
To maintain strict data privacy and regulatory compliance, the interface actively intercepts and masks restricted inputs—like Social Security or credit card numbers—directly inside the message bubbles. It pairs real-time privacy guidance with secure deep-links to billing profiles, protecting sensitive PII without breaking user momentum.
Structuring Automated Fallbacks and Safety Nets
When APIs trigger a no-match state for active bookings, a structured fallback path takes over. Conversely, for high-risk routing scenarios like a medical emergency, intent-classification guardrails instantly override standard automation to surface deterministic safety instructions and offline care numbers.
Demystifying AI Mechanics to Build User Trust
Integrating AI into high-stakes healthcare environments requires proactive system transparency. A dedicated, plain-language FAQ module explains the system's core capabilities upfront—setting clear expectations, reducing user hesitation, and driving adoption.
91%
— Intent Recognition
Elevating accuracy by aligning natural language queries with definitive portal shortcuts.
7.5K+
— Monthly Active Users
Driving self-service adoption through accessible conversational frameworks.
86%
— User Return Rate
Building long-term platform trust and retention through proactive privacy and transparency workflows.
+10 Points
— NPS Increase
Minimizing friction by overhauling care access models and optimizing fallback guardrails.
12%
— Task Completion Velocity
Accelerating successful web and mobile transactions by bypassing legacy, deep-nested portal navigation.
Future Impact & Tracking
— Long-Term Operational Efficiency (Pending Long-Term Data)
Next Phase: Partnering with analytics teams to track live agent volume reduction for routine appointment cancellations, measuring the exact dollar value of automated containment.
Let's hop on a call to chat about how strategic UX empowers us and helps train smarter systems.