A healthcare technology company Doctolib has developed an AI-powered support system called Alfred that functions like a digital butler to handle routine customer inquiries while maintaining strict security protocols.
The big picture: Doctolib’s implementation of an agentic AI system represents a practical application of artificial intelligence in healthcare support, designed to process approximately 17,000 daily messages.
- The system, named Alfred, operates as a network of specialized AI agents working together, each with defined roles and specific tools at their disposal
- By handling routine support queries, Alfred enables human agents to focus on more complex cases requiring personal attention
- The system leverages LangGraph for orchestrating interactions between different AI agents and incorporates a RAG (Retrieval Augmented Generation) engine for improved response accuracy
Technical architecture: The implementation prioritizes security and reliability while maintaining efficient operation.
- Service-to-service authentication is managed through JSON Web Tokens (JWTs), ensuring secure communication between system components
- AI agents operate with inherited user permissions rather than administrative access, maintaining security boundaries
- The system includes fact-checking mechanisms and human-readable confirmations before executing sensitive actions
- Large Language Models (LLMs) are restricted from directly executing sensitive operations to prevent potential errors or security risks
Performance monitoring: Doctolib has established clear metrics to evaluate the system’s effectiveness and efficiency.
- Success is measured on a 1-3 scale to assess the level of achievement in handling support requests
- Efficiency metrics track both latency and the number of steps required to resolve inquiries
- The system’s ability to handle high message volumes (~17,000 daily) demonstrates its scalability
Real-world application: Alfred functions as an intelligent support system capable of understanding and addressing user needs effectively.
- The system can guide users through complex processes, such as managing calendar access rights
- User context is maintained throughout interactions to ensure appropriate and personalized responses
- The RAG engine enables accurate information retrieval and response generation based on existing knowledge
Looking ahead: While Alfred represents a significant advancement in AI-powered healthcare support, its current implementation serves as a foundation for future expansion.
- Doctolib continues to identify opportunities for expanding Alfred’s capabilities and use cases
- The successful deployment demonstrates the viability of agentic AI systems in handling sensitive healthcare-related support tasks
- Future developments will likely focus on enhancing the system’s ability to handle increasingly complex support scenarios while maintaining security and efficiency standards
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