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Nightly price intelligence pipeline that scrapes 15 consumer electronics products across 13 retailers (Amazon, Best Buy, Walmart, B&H Photo, Adorama, Newegg, etc). Each store gets its own isolated scraper actor so a DOM change on one site doesn't take down the whole batch. Prices are normalized at scrape time (unit vs bulk), tracked over 30-day windows, and surfaced in a dark-theme dashboard with per-product trend lines and savings alerts. Exports to CSV for downstream analysis. Python + FastAPI backend, BeautifulSoup with fallback selectors, Chart.js frontend. Scheduled via cron at 03:00 UTC with retry and exponential backoff on failures.
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Built a simple lead intake and follow-up workflow for Nightstack Labs.
The goal was to make handling new customer inquiries more organized without manually moving information between different tools.
The workflow:
Customer submits a form
→ lead information is organized
→ lead is logged
→ the business gets notified
→ the customer gets a confirmation
Built with Tally, Make, Google Sheets, and Gmail.
AI can also be used to summarize incoming requests when it actually improves the workflow.
I like how the form feeds straight into a sheet and triggers the email, cutting out the copy paste step.