Case Study: US-based Commercial Liability Insurance Company achieves ML-powered personalized insurance package selection with Intetics

Insurance Company Leverages Automated Web Data Collection And Data Analytics To Personalize Package Selection

US-based Commercial Liability Insurance Company sought to build an ML-powered recommendation system to help SMBs choose personalized insurance packages faster and more accurately, but lacked the industry-specific datasets needed to train models. The company engaged Intetics to set up the process and handle research, automated data collection, verification and cleansing.

Intetics deployed an Offshore Dedicated Team and a hybrid automated/manual workflow (using C#, SQL, Selenium, HTML Agility Pack) to analyze over 1M websites and deliver 451K records overall. Intetics delivered an initial 27K-record dataset then additional 233K and 191K sets, subsequently producing consistently over 100K rows per dataset and one production-ready dataset per month—reducing costs and timelines, enabling a 12‑minute insurance package definition, and delivering data quality that met or exceeded the client’s expectations.