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WhatsApp chats piling up at a small business? I built an AI assistant that handles them, with 3 rules it never breaks.
Answer only from the business's own documents, and show the source.
If the answer isn't there, it says so and offers a person. No guessing.
Book appointments step by step, checked against the opening hours.
Sunday? Closed. Friday at 10:30? Recorded, and the owner gets a WhatsApp message.
Hand the chat to a real person the moment the customer asks.
The bot goes quiet, and the owner replies from their own WhatsApp.
The test that surprised me:
Before publishing, I ran real conversations through it. "Quiero hablar con una persona" (Spanish) reached a person. "I want to talk to a person" (English) didn't: the bot asked the customer to type "human". English was missing the word "person". Fixed, with a test so it can't come back.
Under the hood: Python, FastAPI, the official WhatsApp Cloud API and Claude, plus an offline mode that needs no API key. Signed webhooks only, no double replies, flood control. 245 tests, 98% coverage.
Full case study and code: https://contra.com/p/YAEPQRqk-whats-app-ai-assistant-answers-booking-handoff
Does your team answer the same WhatsApp questions every day? Send me your top 5 and I'll tell you which ones a bot can answer safely.
The detail about the English trigger failing while Spanish worked is a perfect example of why multilingual edge cases break production systems. Standardizing the handoff phrase across all supported languages prevents that kind of silent failure.
Exactly. The fix went beyond adding "person": "someone", "alguien" and "alguém" now count only next to a verb like "talk", so "Can someone else bring my child?" doesn't hand the chat off by mistake. Each language now has its own handoff tests, plus cases that must not trigger....
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