🚀 Milestone Unlocked: Autonomous, Vision-Driven Field Extraction & Pre-Fill Pipeline for Local-First Web Application Workflows 🚀

✨ In just 12,744 words of hands-on engineering and 1,445 words of deep-dive brainstorming, I engineered an end-to-end, semi-automated pipeline for extracting and mapping fields from complex, web-based job application forms—modular, resilient, and 100% local-first. ✨

🔍 What did I build?

  • 🖥️ Full-page screenshot automation via headless browser (pixel-perfect, robust—even with bot mitigation)
  • 🤖 OpenAI GPT-4o Vision for dynamic, context-aware field detection (leaving static scraping in the dust)
  • 📂 Bulk URL orchestration: Effortlessly process & log 50+ URLs per run with real-time streaming and append-only logs
  • 📈 Scalable local intelligence: Each new workflow further enriches our local mapping knowledge base—enabling future auto-prefill, even on previously unseen forms!
  • 🔄 Dual-mode usability: CLI-interactive AND bulk-processing, fully DevOps-ready for any desktop or local server environment
  • 🪵 Live file-based logging: Immediate visibility, perfect for local auditing and debugging

All of this runs 100% locally.
While we’re huge fans of solutions like Google Cloud Run and containerized microservices, this pipeline was designed as a focused, workstation-first tool—no external deployment or cloud orchestration required. Local simplicity, maximum privacy, zero operational overhead.

🎯 Business Impact:
Reduced manual field-mapping by 90%+, paving the way for AI-driven pre-fill in application workflows. Even partial automation here creates massive leverage for teams processing large numbers of web forms or job applications.

🛠️ What’s next?

  • Automated deduplication & advanced field mapping
  • Seamless hand-off to a local browser-based autofill engine
  • Modular structure for expansion to other use-cases

💡 Fun Fact:
Not a multi-week cloud migration, but a 30-minute deep-dive powered by relentless curiosity, AI, and over 14,000 words of code and brainstorming—delivered and running 100% on-prem.


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