Architecture of an AI chatbot for WhatsApp
An AI chatbot for WhatsApp has three main components: the message receiving/sending layer (Chat API), the language understanding layer (NLU engine like Dialogflow, Rasa, or directly GPT-4 API), and the business logic layer.
The NLU engine choice depends on the use case.
GPT-4 integration with WhatsApp
GPT-4 integration with WhatsApp Business API via Chat API creates virtual assistants that understand complex requests and respond contextually.
Maintain conversation context: each message must include the history of the last N interactions.
RAG (Retrieval Augmented Generation) for FAQ
For an accurate FAQ chatbot, use RAG: embed your support documents in a vector database, and when a question arrives, retrieve the most relevant chunks to use as context for GPT-4.
Metrics and continuous improvement
Monitor chatbot quality with these metrics: escalation rate, first contact resolution rate, average CSAT post-chatbot conversation, and conversation abandonment rate.
