If your workflow involves reading images, documents, or camera 
feeds manually — that can be automated.

I build computer vision systems that process visual input and 
extract useful information from it. Number plates, invoice text, 
form fields, product labels, scanned documents — these are all 
just patterns that a well-trained pipeline can read faster 
and more accurately than a human doing it manually.

My TrOCR Document Extraction project pulls structured data from 
scanned documents end to end. My Number Plate Detection pipeline 
identifies and reads plates from image input using OpenCV and 
deep learning. Both are on GitHub and demonstrate what a 
complete vision pipeline looks like in practice.

What I build:
OCR pipelines for PDFs, invoices, receipts, and scanned forms.
Object detection systems for products, plates, or custom targets.
Image classification for sorting or quality control workflows.
Document AI that extracts structured fields from unstructured 
visual input.

If you have a manual step in your business where someone reads 
something from an image or document — that step can be automated 
with a properly built vision pipeline.