Case Study: Coffee Meets Bagel achieves fewer fake profiles and faster, more accurate fraud reviews with Sift

How Coffee Meets Bagel safeguards its community for users truly looking for love

Coffee Meets Bagel is a dating app that curates daily, high-quality matches to help people find real relationships, with over 150 million matches to date. The company faced a growing problem of fake profiles and romance scams that undermined user trust and strained manual, rules-based review processes as fraudsters quickly adapted.

By partnering with Sift and its real-time machine learning, CMB now proactively detects and auto-blocks fraudulent users before they can harm the community, layering Sift on top of internal tools. The result is a faster, more accurate review workflow, a drastic reduction in reported scammers, and an improved experience for users genuinely looking for love.

Coffee Meets Bagel

Dawoon Kang

Chief Dating Officer and Co-Founder