Neovance:
Pioneering Agentic AI for Patient Assistance Programs
How Neovance deployed Nova 2 Sonic voice agents for patient support: 14% AI containment and an 84.3% quality score from day one, zero Sev1 incidents.
The Challenge
A major clinical research organization wanted to modernise their Patient Assistance Program (PAP) by migrating to Amazon Connect. Their objective was to introduce an AI-first strategy that could automate inbound patient support inquiries and drive proactive specialty pharmacy outreach, all without sacrificing the empathy and quality of human care.
- Patient Assistance Program required AI-first automation without compromising empathy or care quality
- Specialty pharmacy prescription management was entirely manual and resource-intensive
- No automated patient engagement—all outreach was handled by human agents
- Project timeline compressed by one month due to customer mandated deadlines
- Changing and inconsistent test data during build and UAT phases
- Complex provider queries involving multiple patients per call required careful AI handling
- AI response accuracy impacted by background noise and varying call quality
The Solution
CloudInteract engineered the organisation's first Agentic AI workload, implementing Amazon Bedrock, Amazon Q, and cutting-edge Nova 2 Sonic voice bots. The solution autonomously handles inbound prescription queries while executing proactive SMS and voice campaigns—delivering a highly conversational, automated patient support experience.
- Built and deployed 2 Nova 2 Sonic AI voice agents for patient hub and specialty pharmacy
- Integrated Amazon Bedrock and Amazon Q for intelligent, knowledge-driven responses
- Deployed outbound SMS and voice campaigns for proactive patient engagement
- Built SMS bot for inbound prescription refill requests and outbound status updates
- Integrated with the client's Engagement Platform (CRM) and Enterprise Pharmacy System
- Delivered Apollo by CloudInteract for AI call analytics, containment tracking, and QM scoring
- Achieved 14% AI containment from Day 1 with a clear optimisation path identified
- Client empowered to control AI knowledge base independently via amendable articles
Results
The service opened at roughly 14% containment on day one, 611 of 4,236 calls, and has since sustained 30%. That trajectory matters more than either number on its own. The common failure in agentic deployments is not a bad launch, it is a launch that never moves, because nobody owns the loop between what the agent got wrong and what changes next. Containment here means the caller completed their query with the AI and hung up. It excludes calls that started with AI and transferred to a person.
Why CloudInteract
CloudInteract took a risk-aware, delivery-led approach. Extensive internal testing across the company identified and remediated issues before external UAT, resulting in very few failures during client testing. A formal Risk Acceptance document addressed AI's inherent limitations and helped the client understand and accept the technology. The project was re-baselined and critical scope decoupled when the timeline was compressed by one month.
Project Timeline
Analysed common patient queries via Apollo CX Insight and built knowledge base architecture
Built conversational IVR, integrated CRM & pharmacy systems, and deployed Nova 2 Sonic agents
Extensive company-wide testing across scenarios, latency, accents, and edge cases
Client UAT with locked test data set and formal AI risk acceptance documentation
Successful Day 1 with zero Sev1 incidents, only 7 tickets logged post go-live (3 due to incorrect client data)
Ongoing AI tuning with intent-level analysis to improve containment beyond initial 14%
Technology Stack
Key Results
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