Developing a dating platform like Con-tact involved addressing multiple layers of complexity simultaneously. The application needed to process high volumes of user-generated images and videos while ensuring that all content adhered to community guidelines—without introducing any perceptible latency into the user experience. This required integrating AI-powered moderation tools capable of detecting faces, flagging unsafe or inappropriate media, and preventing harmful content from ever reaching the public feed.
On the backend, a hybrid database model had to be implemented to handle both relational and non-relational data efficiently at scale. The infrastructure also needed to be cloud-based, highly available, and horizontally scalable to support thousands of concurrent users without degradation in performance. Finally, the deployment process demanded a robust DevOps workflow—one that could support rapid feature releases and infrastructure changes while ensuring zero downtime for active users.
Stable, high-performing backend successfully supporting thousands of concurrent users with consistent response times across all core features
Automated AI moderation reduced manual content review workload by 80%, enabling the trust and safety team to focus on edge cases and policy refinement
Increased user trust through verified, AI-screened media uploads—significantly reducing reports of inappropriate content from day one
Optimised data storage and retrieval speeds across both MongoDB and PostgreSQL, ensuring fast profile loads and seamless match interactions
Admin panel streamlined content review, user management, and moderation workflows—giving the operations team clear oversight and fast response capabilities
