Quantity and unit price can swap places without changing an invoice total.
At Procys, my document AI work connects OCR and LLM layout reasoning with deterministic validation, field confidence and exception review.
Here's a test case I'd include before connecting a new supplier layout to accounting software. A synthetic invoice shows 2 units at £50 each. The extractor swaps the fields to 50 units at £2. Both produce £100, so a line-total check alone misses the error.
I'd check quantity and unit price against the source columns, then route an ambiguous row to a reviewer with its document context. The acceptance check should cover what the next system will do with each field.
A research-assistant project exploring how AI applications can retrieve information and improve the quality of their responses through a self-correction workflow.
Project focus
Python-based AI application development.
Retrieval and research workflow design.
Improving answer reliability through evaluation and correction.
Description: I turn messy spreadsheet exports into clean, consistent, analysis-ready data. I remove duplicates and extra spaces, standardize names, dates and currency, and flag missing values for review instead of guessing.
Tags: Data Cleaning, Excel, Data Formatting, Data Entry, Spreadsheets, Virtual Assistant
Your competitors can change their prices overnight. Your data collection system shouldn't miss it. 📊
Imagine checking 50 product pages every morning just to find out which prices have changed.
Now imagine getting that information automatically.
With Python web scraping and automation, businesses can build systems that:
→ Monitor product prices across multiple websites
→ Track stock availability
→ Compare competitor pricing
→ Record changes over time
→ Send alerts when something important changes
→ Export updated data to Excel or CSV
Instead of repeatedly checking websites, you get organized information that helps you make better business decisions.
This can be especially useful for e-commerce businesses, online retailers, and teams that regularly research competitors.
At ScrapePro Solutions, I build custom Python scraping and automation solutions tailored to specific business needs.
A quick question for e-commerce business owners:
If a competitor changed their product price today, how would you find out — manual checking or automatic alerts?
Two things bit me while building a price tracker. A page can come back "successful" but empty (in my case, compressed content the client couldn't decode), and saving that blindly overwrites good data. So I refuse any page with no title and no price, and only record a change when...