Case Studies

An automotive platform needed two things at once: structured lead data from 1,500+ dealer websites across Europe for sales outreach, and comprehensive pricing data to build an internal pricing model. Every dealer site was different. Different layouts, different CMS platforms, different ways of listing inventory and contact details. Manually researching even a fraction of these sites would take months, and the data would be outdated before the team could act on it. They needed a way to extract, clean, and structure data from all of these sites at scale, without building and maintaining 1,500 individual scrapers by hand.

A travel newsletter startup built its audience by sharing incredible flight deals. Error fares, flash sales, and underpriced routes that most travelers would never find on their own. The problem was finding them. The founder was spending hours every day manually scanning booking sites, comparing prices, and cross-referencing historical averages to spot genuine deals. It was inconsistent, time-consuming, and didn't scale. As the newsletter grew, covering more departure cities and destinations became essential, but doing it manually meant either hiring a team or missing deals. They needed an automated system that could monitor hundreds of routes around the clock and reliably surface only the deals worth sharing.