n8n WhatsApp AI Agent
Multi-Modal Automation with Google Gemini
Sophisticated n8n workflow creating an intelligent WhatsApp bot with multi-modal capabilities. Processes text, voice, and images using Google Gemini AI. Features smart routing for message type detection, real-time voice transcription, image analysis, and conversation memory management. Fully integrated with WhatsApp Business API.
Why it mattered
Handles text, image, and voice inputs in one documented workflow
What shipped
Sophisticated n8n workflow creating an intelligent WhatsApp bot with multi-modal capabilities. Processes text, voice, and images using Google Gemini AI. Features smart routing for message type detection, real-time voice transcription, image analysis, and conversation memory management. Fully integrated with WhatsApp Business API.
Proof signal
Handles text, image, and voice inputs in one documented workflow
System flow
Message Trigger -> Type Detection -> Media Download -> AI Processing -> Memory -> Response.
Honest maturity snapshot
Manual questions, scattered context, and slow follow-up.
An agent workflow that routes intent, calls tools, and returns useful next actions.
Features
- n8n integrated into the workflow.
- WhatsApp API integrated into the workflow.
- Google Gemini integrated into the workflow.
- Workflow Automation integrated into the workflow.
- Message Trigger stage documented in the delivery flow.
- Type Detection stage documented in the delivery flow.
Engineering challenges
- Keeping the implementation clear enough to explain while still solving the core technical problem.
- Choosing a scope that could be shipped, tested, and documented.
- Turning technical work into proof a visitor can evaluate quickly.
Results
- Handles text, image, and voice inputs in one documented workflow
- Documented the engineering path and important learnings.
- Made source code or technical proof available for review.
What I learned
- Tradeoff learned: Keeping the implementation clear enough to explain while still solving the core technical problem.
- Proof learned: Handles text, image, and voice inputs in one documented workflow
- Next iteration: Add richer screenshots or a narrated demo.