Applied AI & Workflow Automation
Automating Purchase Order Processing with an AI Agent
Context
Within customer success operations, purchase order processing required manual email triage, document extraction, standardized file naming, and organized storage. This repetitive workflow created unnecessary friction and delayed downstream execution.
Problem
Purchase orders arrived via email in inconsistent formats and required manual review, renaming, and filing. The process was time-intensive, prone to inconsistency, and slowed internal coordination.
Opportunity
Design a production-ready AI workflow that could:
Detect relevant purchase order emails
Extract key information
Apply standardized naming conventions
Automatically file documents into structured cloud storage
Draft response confirmations when appropriate
Solution Architecture
Using n8n as an orchestration layer, I built a multi-step AI agent integrating:
Gmail API for inbox monitoring and retrieval
Anthropic LLM for content parsing and conditional decision logic
Google Drive API for structured document storage
The workflow includes:
Conditional branching logic for PO detection
LLM-based extraction of relevant metadata
Automated document renaming and folder routing
Draft email response generation
Error handling pathways for ambiguous inputs
The agent runs in production and supports daily operational workflows.
Product Capabilities Demonstrated
AI workflow orchestration using n8n
Multi-step conditional logic design
API integration across Gmail, Anthropic, and Google Drive
LLM prompt engineering for structured extraction
Production deployment of automation systems
Converting manual processes into scalable internal products
Impact
Reduced manual email triage time
Standardized file naming and storage conventions
Accelerated internal response cycles
Clarified undocumented process assumptions through structured agent design
In documenting and building the workflow, I translated implicit team behavior into explicit system logic, improving overall process clarity.