Clinical research data published on institutional websites is some of the most structured, high-value information available publicly. Extracting it at scale, however, has traditionally required either manual copy-paste or fragile custom scrapers that break the moment a page layout changes. This guide shows how to extract clinical trial listings from UCSD Clinical Trials (the official trial browser at clinicaltrials.ucsd.edu/browse/) using the Minexa API — a data extraction pl

VesselFinder tracks hundreds of thousands of ships worldwide. The vessel list at vesselfinder.com/vessels is one of the most complete public directories of maritime assets available, covering cargo ships, tankers, cruise liners, and more. Getting that data into a spreadsheet for analysis, research, or fleet monitoring normally means a lot of manual copying. This tutorial shows how to do it automatically using the Minexa Chrome extension. What data you can extract from VesselF

Collecting job market data from Jora manually is slow, inconsistent, and breaks the moment you need more than a handful of listings. The Minexa API gives developers a repeatable, structured extraction pipeline that works across thousands of pages without writing a single selector. This guide covers the full workflow: training a scraper on Jora, retrieving your scraper_id, and calling the API to extract job listings at scale. What data Jora exposes Each listing on a Jora searc

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