Case Study
Autonomous 6-Step AI Pipeline with n8n Orchestration
An end-to-end automation system that replicates the work of a senior content strategist. Uses n8n workflow orchestration, OpenAI APIs, and Apify scraping to generate production-ready content calendars with complete briefs, captions, and hashtags.
Content creators and agencies spend 20+ hours per week researching competitors, analyzing trends, and planning content calendars. The manual process is inconsistent, misses opportunities, and cannot scale across multiple client accounts. The client needed an automated system that could replicate the strategic thinking of a senior content strategist.
I built an end-to-end AI-powered content strategy automation using n8n workflow orchestration and OpenAI APIs. The 6-step pipeline autonomously scrapes competitor content via Apify, extracts Brand DNA, analyzes trends, generates production-ready content briefs with captions and hashtags, runs QA validation, and outputs a full content calendar - all with rate limiting, caching, and error recovery.
20+ hrs/week
Time Saved
Per client account
6
Pipeline Steps
Fully automated
2
Output Formats
JSON + Markdown
24 hrs
Cache Duration
Intelligent refresh
The system uses n8n as the workflow orchestration engine, with custom TypeScript nodes for specialized processing. The pipeline flows through 6 sequential AI steps: Brand DNA extraction analyzes client positioning, Competitor Intel scrapes and analyzes 5 competitor accounts via Apify, Trend Analysis identifies content patterns, Production Briefs generates 14 detailed content pieces, QA Validation ensures brand consistency, and Calendar Generation schedules the month. Rate limiting with progressive backoff handles OpenAI API constraints.
Challenge
Handling OpenAI API rate limits on worst-tier accounts
Solution
Implemented progressive rate limiting with configurable delays (default 90s between calls), exponential backoff on failures, and batched processing. The system gracefully degrades rather than failing completely.
Challenge
Maintaining context across 6 AI pipeline steps
Solution
Designed each step to output structured JSON that feeds into the next step. Used consistent schema contracts between steps and implemented validation to catch malformed outputs early.
Challenge
Scraping Instagram data reliably without getting blocked
Solution
Integrated Apify Instagram scrapers with intelligent request throttling. Implemented 24-hour caching to minimize scraping frequency while keeping data fresh for strategy decisions.
Centralized patient flow aggregation platform using real-time web scraping from 26 hospital emergency departments. Achieves 99.9% data accuracy through per-hospital schema mappings and validation pipelines.
UNFCCC - Automation Engineer. Chrome extension with Node.js and Puppeteer that replaced manual stream monitoring with automated quality checks and fast alerts.