Turn webpages into LLM-ready data at scale with a simple API call
Turn webpages into LLM-ready data at scale with a simple API call
“ScraperAPI’s seamless integration made it quick and easy to start. In just a couple of minutes, we started seeing our success rates increase, and as our data demands grew, ScraperAPI’s scalable infrastructure consistently helped us bypass website blocks.”
Dotlas is a data and intelligence platform that empowers restaurant operators with actionable insights grounded in big data food industry analytics to optimize performance, pricing, and competitive growth.
Founded by two well-verse data professionals from Ubereats, Dotlas had the necessary technical and industry experience to become the #1 source of intelligence for businesses in the food and beverage industry.
For such a fast-paced industry, where prices, consumer trends, and competitors shift constantly, getting practical insights for retailers would mean collecting a massive amount of data across public datasets, census data, restaurant websites, news articles, promotional materials, and more.
However, Eshwaran, Dotlas’s CTO and co-founder, soon realized that getting access to public data on a large scale wouldn’t be as simple.
Most of these sites use advanced anti-bot blockers, which prevented the team from gathering this information consistently and at the right speed to provide meaningful intelligence.
If they wanted Dotlas to work, they needed to find a solution, fast.
To collect the data at the scale and speed we wanted, we needed a robust solution to ensure our web scraping efforts weren’t hampered by IP blocks or CAPTCHAs. These challenges could easily break our scrapers, making our datasets incomplete.
Eshwaran Venkat
CTO and Co-Founder at Dotlas
ScraperAPI has transformed Dotlas’ web data-gathering operations, offering powerful value and customization. It is user-friendly, dependable, and minimizes risk. It is an essential tool that keeps our insights timely, precise, and free from the challenges of data-gathering at scale
Eshwaran Venkat
CTO and Co-Founder at Dotlas
The Dotlas team integrated ScraperAPI into their infrastructure “using a simple API key and customizable headers.”
By making all their requests go through the API, ScraperAPI advanced bypassing automatically handles IP and header rotation, generates cookies, handles CATPCHAs and rendering, and much more.
Thanks to this quick integration, Eshwaran and his team could scale their existing infrastructure without any big disruption to their codebase, saving hundreds of hours of work and giving them the consistent access to public data he needed.
ScraperAPI is now a core component of Dotlas data collection infrastructure. They rely on it to handle a high volume of requests, often on an hourly basis, ensuring a constant flow of data for their analysis.
In Eshwaran’s words:
“ScraperAPI has given us confidence in our data collection process, allowing us to automate data gathering and make faster, more informed decisions.”
Let our experts build a custom plan that fits your needs, including a dedicated account manager, Slack support channel and all premium features ScraperAPI has for you.
