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- The client required a generative AI assistant to interact with users and provide guidance on cold therapy.
- Needed a solution to answer user queries related to therapy in a natural and conversional way.
- Aimed to enhance patient support services and streamline operations with an automated AI assistant.
- Streamlined solution to ensure accuracy, reliability and ease of use in healthcare-related contexts.
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We initiated the project by understanding the requirements and setting the product backlog.
The solution used LangChain for efficient processing of large user queries and answers accordingly through AI assistant.
The AI assistant can take queries in multiple languages but answer them only in English language.
The solution used Azure OpenAI's GPT-4 Omni models (up to 32,000 tokens) to enable intelligent, responsive user interactions.
Used SQL Server for chat data storage, Redis for real-time caching, and Celery for async query processing.
Used Azure Search Index for storing the vector representation of the knowledge dataset.
Improved Patient Engagement
Achieved significant improvement in patient interaction rates and overall satisfaction through enhanced service delivery.
Operational Efficiency
Streamlined patient support operations with reduced call center workload and faster query response times.
Data-Driven Insights
Enhanced decision-making capabilities through advanced data analytics and comprehensive AI-driven business intelligence insights.
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