AI-Scored Upwork Lead Pipeline: Apify Actor → GPT Scoring & Enrichment → Google Sheets

Problem: Hunting new Upwork jobs for makeup-artist (MUA) work meant manually browsing listings every day, filtering out mismatches by eye, and copy-pasting promising posts into a tracking sheet, with no systematic way to score fit or capture full job details.

Solution: Built an n8n workflow triggered on a schedule that fires an Apify Actor to scrape Upwork job listings and returns the raw dataset via Get dataset items. A Google Sheets node reads the current tracking rows, a JavaScript Code node dedupes against them, Edit Fields normalizes the payload, and a Limit node caps the batch. The cleaned jobs feed into a first OpenAI node ('Scoring and filtering') that scores each job for fit and writes a Response Text, a Filter node drops jobs below the threshold, then a second OpenAI node ('Job details') enriches the survivors with structured detail extraction before an Append or Update Row node writes the scored, enriched records back into Google Sheets.

Result: Qualified Upwork jobs now land in the tracking sheet pre-scored and enriched on every schedule run, replacing manual listing review with a filtered, prioritized lead pipeline.