Engineering Digital Products
Fully automated pipeline that turns structured question data into branded MCQ videos and publishes them to YouTube on a schedule, zero manual editing.
Producing educational quiz videos manually, scripting, rendering, thumbnailing, uploading, was consuming hours per video for what should have been a repeatable, templated process.
We built a Python desktop automation tool using MoviePy and PIL to render MCQ, logical-reasoning, and visual-question videos from a templated design system, queued through Firebase Realtime Database and orchestrated by Firebase Cloud Functions for batch scheduling. Finished videos publish directly via the YouTube Data API v3, with email alerts on quota events and a PyInstaller-packaged build for non-technical, day-to-day operation.
Automated MCQ Video Rendering (MoviePy + PIL)
Multiple Question-Type Templates
Firebase RTDB Job Queue
Cloud Functions Batch Scheduling
Direct YouTube Data API v3 Publishing
Quota Email Alerts
Configurable Poll Intervals
Packaged Desktop App (PyInstaller)
"Eliminated manual video editing and upload work entirely, what was a multi-hour-per-video task became a queue-and-forget pipeline running on a schedule."
Designer eyewear store with browser-based AR try-on, letting shoppers see frames on their own face before buying online.
AI-powered extraction pipeline that turns raw PDFs, spreadsheets and CSVs into clean, structured question banks, no manual data entry required.
Whether you need a robust ERP, a customer-facing app, or a scalable SaaS platform, we have the engineering expertise to build it.
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