Most support teams have access to more data than they can actually use. The tickets are there, the comments are logged, the status changes are recorded, and the SLA fields are populated. The problem is not that the data does not exist. The problem is getting it out in a shape that is actually useful for analysis. This is a workflow that comes up repeatedly in support operations and QA contexts: a lead needs a weekly or monthly spreadsheet with full ticket comments, status his

Most data extraction pipelines start the same way: someone needs structured data from a website, and the first instinct is to write a scraper. Then comes the selector logic, the edge cases, the JavaScript rendering layer, the proxy setup, and eventually a fragile script that breaks when the site updates. The Minexa API was built to replace that entire process with a single trained scraper and a POST request. This guide walks through exactly how that works, from training your