Data Cleaning & Training-Data Pipelines

Turn messy records and raw media into clean, traceable data you can train on or run a business on.

Most data problems start before any model is trained. Records come from old spreadsheets, PDFs and supplier sheets in different layouts, with typing differences and duplicates. We build pipelines that bring this data in, clean it, and keep it in one standard format.

In one project for a building-material distributor in Canada, we cleaned and standardised 20 years of sales and inventory data, removed duplicates, and wrote logic that reads updated supplier sheets from PDF or Excel files with different layouts into the same format every time. The clean data then showed seasonal patterns the team could use for buying and advertising.

The same discipline applies to training data. Our own tools move closed or duplicate records into a separate quarantine file instead of deleting them, and our media QC tool checks AI-generated images and video against references, then writes a signed record of where each file came from. You get clean data and a clear trail of what was removed and why.