The way woman was created carries deep meaning:
- She wasn’t made from his head (to rule over him) or his feet (to be beneath him), but from his side, to be equal to him, close to his heart, under his arm for protection.
- Together, Adam and Eve were made in God’s image.
I got tired of context-switching just to understand what's in my inbox.
So I built a lightweight AI pipeline that automatically reads, summarizes, and structures every incoming email (zero manual effort).
What's next:
Adding an AI classification layer: a secondary LLM call that labels each email by category: ( Payment | Support | Lead | Newsletter | Spam )
This turns the pipeline into a full intelligent inbox router, not just summarization.
This is the same pattern behind AI automation systems. Once you internalize it, you can apply it almost anywhere:
Customer support triage
Payment & transaction alerts
Inbound lead classification
Complaint detection & escalation
Stack:
n8n - workflow orchestration
Gmail API - event-driven email trigger
OpenAI API - LLM-based summarization
Google Sheets API - structured data sink
JavaScript - payload normalization & transformation
When a new email lands:
- Gmail API fires a webhook trigger on message receipt
- A JavaScript transformation layer parses and normalizes the payload, extracting sender metadata, subject, timestamp, and raw message snippet
Here's the full architecture:
Pipeline: Gmail Trigger => Data Extraction => OpenAI Inference => Google Sheets Persistence
The pattern that makes this powerful:
Trigger => Extract => Infer => Store