Alex M.

Developed a high-load data scraping tool for extracting contact and property information using unique credentials for 1,000+ customers. Built an automated pipeline converting scraped data into CSV format and uploading it directly into the client’s system. Implemented scheduled scraping (daily/weekly/monthly), robotic process automation, and error-resilient workflows to minimize manual intervention. Ensured reliable performance, seamless system integration, and full support for ongoing data extraction operations.

The Client wanted to build a software solution to assist brands and agencies with their influencer marketing campaigns by offering massive searchable databases of potential influencers, using AI algorithms. We helped to develop an interactive B2C web application while optimizing the speed of data loading that allowed customers to quickly identify and target the right individuals for their campaigns, potentially saving them time and resources.

This project involved developing a tailor-made data analysis tool for a U.S. insurance provider who were facing challenges analyzing a significant volume of data. The Client needed a professional and customized solution which would enable effective analysis of their data and provide actionable insights to improve their business operations. Our solution delivers real-time processing of data, flexible filtering capabilities through dashboards, and also supports dashboards detailing the evaluation of insurance loss or profit by industry vertical. Additionally, a predictive model for profitable insurance cases was built using historical data, and a reporting system was created to show significant factors and profitability based on different metrics.