DTM (Dating to Marry)
DTM (Dating to Marry) is a relationship-focused app for people seeking a life partner. It automatically filters profiles based on a user's interests and personality to surface highly compatible matches, ensuring users only see high-quality candidates who are genuinely on the same page.
Matching Hearts with Intelligent Precision
- The Challenge The core problem was finding and recommending the best-matching users to each individual based on their specific preferences — at scale, and without ever leaving a user with an empty match list.
- Complexity and Innovation User data is streamed continuously through MongoDB, and each user is matched against a pool of candidates up to a defined limit. When the best-fit pool is exhausted, the system applies progressive filter relaxation to widen the search. If matches are still unavailable, a retention-based fallback logic kicks in — ensuring users are never left without recommendations for the duration of their active retention period.
- The Process We worked with the client to understand their vision for the matching experience, then researched how existing dating platforms structure their recommendation engines. Based on those findings, we built the system using FastAPI for the API layer and MongoDB for real-time data streaming and storage.
- Smart Matching for Meaningful Connections By combining real-time data streaming with adaptive filtering logic, DTM continuously delivers relevant matches while keeping the experience personal and responsive.
Feature Inventory
Enhancing Compatibility Through Intelligent Matching DTM's matching engine is built to stay accurate under changing user pools while never leaving a user without options.
- Real-time user data streaming via MongoDB for dynamic matchmaking
- Preference-based matching engine aligned to user interests and personality
- Progressive filter relaxation to avoid empty match results
- Retention-based fallback logic ensuring continuous match availability
- Scalable serverless architecture using AWS Lambda
- FastAPI-powered backend for fast, reliable matching responses
Great matchmaking isn't just about filtering data — it's about making sure no one is ever left without a possibility.
Redefining Modern Matchmaking
Blending Data Intelligence with Human Connection We designed DTM's backend to feel effortless to the user while running sophisticated matching logic behind the scenes.
- Real-Time Data Streaming: Continuous ingestion of user profiles via MongoDB.
- Personality-Based Matching: Algorithms rank compatibility using interests and personality traits.
- Adaptive Filter Relaxation: Gradually broadens criteria to avoid match droughts.
- Retention-Driven Fallback: Keeps users engaged with fresh matches throughout their retention window.
- Serverless Scalability: AWS Lambda scales automatically with user demand.
- Seamless API Integration: FastAPI enables fast, reliable, and flexible matching responses.
Conclusion
Delivering Meaningful Matches at Scale DTM transformed how users experience matchmaking — consistent, relevant, and never empty-handed.
- Improved Match Quality: Users consistently received highly compatible matches.
- Continuous Engagement: Retention logic ensured users were never left without options.
- Scalable Infrastructure: Serverless design supported a growing user base.
- Faster Matching: Real-time streaming enabled quicker match delivery.
- Data-Driven Personalization: Preference-based filtering improved user satisfaction.