Answer WhatsApp customer questions and escalate to humans
Case study takeaway: an n8n workflow takes each incoming WhatsApp message and assembles the conversation history plus the company knowledge base. OpenAI sketches a reply grounded in that content, and a confidence check decides whether it can be answered reliably. The README gives no measured results, only design goals: cover routine questions, give round-the-clock coverage, and keep a human on unreliable cases.
- Agent or tool
- n8n
- Topic
- Research & Data
- Reported on
- GitHub
- Added
- 2026-10-15
Why it matters
Research is mostly gathering, cleaning and comparing. Handing that groundwork to an agent leaves the person with the part that needs judgment: deciding what the findings mean. It is one of 67 sightings filed under Research & Data on Agent Sightings (number 46 by interest), and one of 36 involving n8n.
How you could try it
Here is a reusable prompt, written by us in our own words, that captures the task. Paste it into n8n or any similar agent and adjust the details to your situation.
Research brief: answer WhatsApp customer questions and escalate to humans. Prefer primary sources, include links and confidence notes, and do not contact anyone.
Tip: Start small: run it once on a low-stakes example, read what the agent did, and only then let it run on real work.
Source
Read the original first-hand account on GitHub: https://github.com/zezo640/whatsapp-ai-support-agent-n8n. Our summary is a paraphrase; details are in the source.