AI Repair Shop Assistant: Full Customer Journey on WhatsApp (n8n + AI Agents) I built an AI syste...AI Repair Shop Assistant: Full Customer Journey on WhatsApp (n8n + AI Agents) I built an AI syste...
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AI Repair Shop Assistant: Full Customer Journey on WhatsApp (n8n + AI Agents)
I built an AI system that runs a repair company's entire customer process automatically, over WhatsApp.
The problem
A device repair business has to handle many customers at once. Taking in details, sending quotes, chasing approvals, tracking parts, telling people when to pick up, and asking for feedback. Doing all of this by hand is slow and things get missed.
What I built
One large n8n system with a team of AI agents, each doing one job.
Takes in new customers through a webhook and creates their record
Generates a quote PDF and sends it to the customer
Reads the customer's WhatsApp reply and understands what they want (approval, question, complaint, or call request)
Replies in the customer's own language, German, English, or others
Reminds staff when a device is waiting for parts
Creates a pickup code and tells the customer when their device is ready
Waits 7 days after a repair, then asks the customer for feedback
Flags negative feedback as a complaint so the team can act fast
The smart part
Instead of one big confused bot, I used many small AI agents that each handle one clear task. This makes the system reliable and easy to fix. An intent classifier reads every message first and sends it to the right agent.
Tech used
n8n, Google Gemini, WhatsApp (Evolution API), Google Sheets, PDF Generator API, Gmail.
Result
A hands-off assistant that manages the full customer journey from first contact to feedback, so the team can focus on repairs instead of messages.💯
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Polar is a local, privacy-focused AI desktop assistant designed around a futuristic HUD interface and system-level interaction.
The project explored how a desktop AI could understand the user's environment, process visual and voice input, and respond or perform actions without relying entirely on cloud services.
Key features:
Local AI assistant architecture
Futuristic Tauri-based desktop HUD
Screen and contextual awareness
OCR-based extraction of text from the screen
Voice interaction pipeline
AI-powered context processing and responses
System-level desktop interaction and automation
Local/offline model execution
Real-time assistant-style interface
OCR pipeline:
Screen capture → OCR → Context extraction → Local AI → Response/Action → HUD
The project combined AI, computer vision, OCR, voice interaction, desktop application development, and modern UI engineering into a single experimental personal-assistant platform.
My contribution: Architecture, application development, AI integration, OCR functionality, UI/HUD development, and system interaction.