Case Study: Worldwide Staffing Corporation boosts developer hiring efficiency with Filtered.ai

How Filtered was used to evaluate and hire English-fluent developers proficient in Java and Groovy.

Worldwide Staffing Corporation needed a faster, more reliable way to evaluate English-fluent Groovy and Java developers for a client project in Peru, especially because language barriers made technical screening harder. To test whether they could improve hiring efficiency, they partnered with Filtered.ai and used its AI-based assessment platform as part of an experiment against their normal interview process.

Using Filtered.ai, Worldwide Staffing Corporation built a first-round screening that included a spoken English video question, two algorithm questions, and one SQL/database question, then uploaded a client homework assignment for the second round. The results improved across the funnel: first-round pass rates increased from 39% to 50%, second-round pass rates rose from 36% to 60%, and offers increased from 66% to 83%, while also helping Filtered.ai eliminate unqualified candidates and potential fraud earlier in the process.

Worldwide Staffing Corporation