Exploring How AI Can Improve Content and Operational Workflows

My professional use of generative AI began while working with high-volume customer intake at UENI, where I used AI tools to help organize and structure large amounts of business information.

Since then, I've continued developing this skill through hands-on experimentation with n8n, LLMs, APIs, and workflow automation.

The projects below are learning prototypes rather than production systems. I built them to understand how AI-assisted automation can support content, customer service, information processing, and operational workflows.

Prototype 01: AI-Assisted Customer Inquiry Routing

Tools: n8n · Gmail · Google Gemini · LangChain

The Idea

Explore how an inbound customer email could be automatically analyzed and routed through an AI-assisted workflow.

Workflow

The prototype:

  1. Detects a new inbound email.
  2. Passes the message through a conditional workflow.
  3. Uses an LLM to interpret the customer's request.
  4. References structured information provided to the workflow.
  5. Generates a contextual response.
  6. Formats the response for email delivery.

What I Practiced