How Pariti Doubled Its Fill Rate with Qdrant

Pariti, a platform aimed at connecting Africa's top talent with promising startups, faced challenges in managing a rapidly growing applicant pool and maintaining a high fill rate. Originally, analysts spent significant time vetting résumés, leading to fatigue and inefficiencies. Data Scientist Chiara Stramaccioni developed a prototype using Python to rank candidates, proving the concept but not solving scaling issues. To address this, Engineering Lead Elvis Moraa implemented Qdrant Cloud, a managed vector database, allowing Pariti to efficiently handle large volumes of candidate data with low latency. This integration reduced résumé vetting time by 70 percent and increased the fill rate from 20 percent to 48 percent, with analysts now able to focus on coaching rather than administrative tasks. The system's accuracy improved, with 94 percent of high-performing candidates appearing in the top decile of search results, leading to increased confidence in hiring decisions. Pariti plans to expand the tool into a customer-facing portal to further streamline hiring processes and meet future demands, while maintaining cost-effectiveness for African startups.