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Modernizing Pharmaceutical Employee Support with an AI-Powered HR Assistant
Executive Summary
A leading healthcare organization sought to modernize patient appointment management through AI-powered voice automation. Pronix designed a cloud-based virtual health assistant using Kore.ai HealthAssist, Amazon Connect, and an AWS AI reference stack. The solution enables patients to schedule, reschedule, cancel, and retrieve appointment information through natural-language voice interactions while supporting bilingual service, appointment triage, notifications, and escalation to live agents.
Business Problem
- High volumes of routine appointment calls
- Long patient wait times during peak hours
- Limited voice self-service
- Manual appointment administration
- Need for English and Spanish interactions
- Integration with the clinical scheduling environment
- Intelligent appointment triage and live-agent escalation
Business Solution
- Appointment self-service : Schedule, reschedule, cancel, and retrieve appointments through conversational voice interactions.
- Intelligent triage : Assess appointment urgency and guide the patient to the appropriate next step.
- Bilingual access : Support English and Spanish voice journeys through language selection.
- Live-agent escalation : Transfer complex or unsupported requests to Amazon Connect agents.
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Automated notifications : Send confirmations, reminders, and appointment updates through integrated services.
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Patient feedback : Capture post-interaction NPS feedback to support continuous improvement.
Technical Solution
Pronix designed a layered architecture separating patient channels, Amazon Connect contact flows, Kore.ai HealthAssist conversational intelligence, enterprise integrations, and supporting AWS AI and cloud services. The implementation lifecycle includes blueprinting, workflow configuration, API integration, testing, production deployment, and hypercare.
Technologies Used
- Kore.ai platform : HealthAssist, XO Platform, Voice AI, Search AI, Healthcare NLP, Generative AI and LLM orchestration
- AWS AI stack : Amazon Connect, Amazon Bedrock,Amazon SageMaker AI, Amazon Q for Business, Amazon Lex, Amazon Polly, Amazon Transcribe, Lambda, API Gateway, S3, CloudWatch, IAM, KMS
- Enterprise integrations : eClinicalWorks, Appointment APIs, Patient notification services, REST APIs, Identity and middleware
Customer Success Outcomes
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Projected Business Outcomes: The percentages below are implementation targets. Final results must be validated through production analytics and customer-approved measurements.
Strategic Value Delivered
- Digital patient-access foundation : Establishes a reusable voice-AI platform for additional healthcare self-service use cases.
- Contact-center efficiency : Reduces dependency on agents for routine appointment administration.
- Connected patient experience : Links voice, conversational AI, scheduling, notifications, and agent support.
- Scalable healthcare automation : Creates a foundation for provider search, billing, prescription support, and care navigation.
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