Data Cleaning & Training-Data Pipelines

Turn messy records and raw media into clean data. You can trace where it came from, and use it to train AI or run your business.

Most data problems start before any model is trained. Records come from old spreadsheets, PDFs and supplier sheets. Each one has a different layout. People typed things in different ways, and there are duplicates. We build pipelines, which are sets of steps that bring this data in and clean it. They keep it all in one standard format.

One project was for a building-material distributor in Canada. We cleaned and standardised 20 years of sales and stock data, and removed duplicates. We also wrote logic that reads updated supplier sheets into the same format every time. It works whether the sheets come as PDF or Excel files, and whatever their layout. The clean data then showed seasonal patterns. The team could use them for buying and advertising.

We treat training data with the same care. Our own tools do not delete closed or duplicate records. They move them into a separate holding file, called a quarantine file. Our media QC tool checks AI-generated images and video against reference examples. Then it writes a signed record of where each file came from. You get clean data. You also get a clear record of what was removed and why.