Automation Practice · AI Operations
n8n Systems
This case study presents a few current workflows from a much broader n8n practice. The common goal is to turn messy inputs into reviewable operational records that people can trust and continue using.
01 · The problem
Why it exists
Useful automation has to survive inconsistent emails, documents, APIs and platform data. Moving information is not enough. The workflow must normalize it, expose uncertainty and leave a clear human review point.
02 · Ownership
What I built
I designed and built the workflow logic, integrations, data transformations, error paths and review surfaces across these systems.
03 · System
How it works
Examples include Content Factory, a receipt parser using Gemini Vision, airline campaign extraction and daily YouTube performance tracking. The workflows connect REST APIs, Notion, Google Sheets and platform services through explicit operational states.
04 · Evidence
What is proven
- Content operations workflow
- Receipt parsing with Gemini Vision
- Airline campaign extraction
- Daily YouTube performance tracking
- Examples selected from a broader active practice