Document extraction is not the product. The review loop is.
OCR or an AI model can extract fifteen fields from an invoice. That does not make the workflow reliable.
The useful system also knows:
• which fields are mandatory
• which values must match business rules
• when confidence is too low
• how to detect possible duplicates
• where uncertain cases should go
• how a human correction returns to the process
I treat extraction as one component. The actual product is a controlled path from document intake to an accepted record — with uncertain cases visible instead of silently approved.
What if a school's existing CCTV infrastructure could do more than just record footage?
I'm exploring a concept for an AI-powered school safety platform designed to help schools identify potential safety incidents, surface relevant camera feeds, and deliver real-time alerts through one intelligent dashboard.
The vision includes multi-camera monitoring, potential fight and fall detection, incident timelines, voice alerts, and a privacy-conscious workflow with human review.
This is a concept exploration focused on bringing computer vision, automation, and thoughtful product design together.
The big question: What would you prioritise first in a system like this — real-time incident detection, multi-camera intelligence, or a smarter security dashboard?