Gemini API Connected
n8n Webhooks Active
LoRA Training: 87%
6-Stage Loop: Running
2๐Ÿ“ฅ Auto Task Capture + n8n Integration
6 Apps Connected

๐Ÿ”— Connected Integrations (n8n Webhooks)

๐Ÿ“‹ n8n Workflow JSON (์‹ค์ œ ์ฝ”๋“œ)

// n8n Gmail Trigger โ†’ Supabase Insert { "nodes": [ {"type": "n8n-nodes-base.gmailTrigger", "parameters": {"events": ["newEmail"]}}, {"type": "n8n-nodes-base.supabase", "parameters": { "action": "insert", "table": "tasks", "values": "{{$json.subject}}" }} ] }

๐Ÿ“ฅ Captured Tasks (Real-time)

3๐Ÿค– AI Suggestions + Gemini API
3 Recommendations

๐Ÿ“Š Impact Summary

+42%
Potential Efficiency Gain
Time Saved+5.2h/week
Error Reduction-38%
Cost Savings$850/mo

๐Ÿ’ป Gemini Prompt (์‹ค์ œ ์ฝ”๋“œ)

async function getSuggestions(tasks) { const prompt = ` Tasks: ${JSON.stringify(tasks)} Analyze and suggest: 1. Merge (similar tasks) 2. Eliminate (100% automated) 3. Automate (predictable patterns) Return: confidence %, reason, simulation (Time/Error/Cost), 3 alternatives `; return gemini.generateContent(prompt); }
4๐Ÿ“Š Outcome Dashboard + Supabase Analytics
Real-time Tracking
โœ… Success Rate
94.2%
โ†‘ 2.1% this week
โฑ๏ธ Time Saved
127h
โ†‘ 18h this month
โš ๏ธ Error Rate
1.8%
โ†“ 0.5% improved
๐Ÿ’ฐ Cost Saved
$4,280
โ†‘ $620 this month
๐Ÿ“ˆ Automation Progress (Supabase Query)
๐ŸŽฏ Task Distribution
5๐Ÿ”„ Feedback Loop + LoRA Fine-tuning
Personalization Active

โœ… Rate AI Accuracy (๐Ÿ‘๐Ÿ‘Ž)

๐Ÿง  LoRA Learning Progress

๐Ÿ’ป LoRA Training Code

# Hugging Face LoRA Fine-tuning from peft import LoraConfig config = LoraConfig( r=16, lora_alpha=32, target_modules=["q_proj", "v_proj"], lora_dropout=0.05 ) # Per-user model training trainer.train(user_feedback_data)
+๐Ÿข ERP Integration PoC
4 Systems Connected