
ℹThis page is a demo anonymized for portfolio use. Service names, company names, figures and images have all been replaced with samples.
FitMate is a matching & social app that connects people around their activities and hobbies. Onto the like → match → real-time chat experience it layers a point economy, billing, identity verification and community health — designed as a service people can trust and use for the long term.
ActiveLink Co., Ltd. had no existing assets — a completely new venture — so from requirements to the mobile app, API and operations console, we built it in-house from scratch in 10 months. Together we launched a foundation that balances scale and safety.
ActiveLink Co., Ltd. focuses on community businesses that create real-world connections between people. Around the theme of meeting others through hobbies and activities, they envisioned launching a new matching platform that puts safety and peace of mind first.
In general, services in this space must satisfy matching quality, real-time performance, monetization and community health all at once — a domain with high design difficulty. ActiveLink set out to build all of these from scratch under one consistent design philosophy.
Smooth identity verification means only trustworthy matches are shown, so users can step out to meet people with confidence. The key was eliminating impersonators and brokers.
Suggest compatible people from hobbies, area and activity patterns, and done right it cuts wasted swipes and raises the match rate. Recommendation-logic design decides success or failure.
When messages always arrive without delay, conversations never break off and relationships deepen. A real-time backbone stable even under massive concurrency was essential.
Respond quickly to reports and blocks, and done right inappropriate users are removed early, keeping the community safe. The challenge was making moderation operations more efficient.
In response, we built mobile, API and operations management end-to-end in-house — designing and implementing across four areas that balance scale and safety.
| Field | Challenge | Solution |
|---|---|---|
| Matching experience | Wasted swipes, low match rate | Built hobby- and area-based recommendations and a seamless like → match → chat flow in React Native |
| Real-time backbone | Latency under massive concurrency | Stabilized message delivery and presence with Socket.io + Redis, with horizontal scaling |
| Billing & point economy | Balancing monetization and consistency | Managed in-app billing, subscriptions and point balances with transactional consistency |
| Identity verification & operations | Reliability and moderation load | Centralized the identity-verification flow and report moderation in the CMS, with RBAC for permission separation |
Provide a trustworthy space through identity verification and moderation.
Hobby-based recommendations achieved a 24.1% match rate.
Deepen relationships through real-time delivery.
Grow the business on two axes: points + subscriptions.
| Stakeholders | Typically | With ActiveLink | Business impact |
|---|---|---|---|
| User | Anxiety over whether the other person is trustworthy | Reach out with confidence thanks to the verified badge | Higher retention |
| Operations | Report handling was person-dependent and slow | Centralized management, SLA visibility in the CMS | 98.7% handled / 24h |
| Billing & revenue | Hitting a ceiling with a single billing funnel | Multi-track revenue from points + subscriptions | Payment rate 6.4% |
| Safety & security | Risk of becoming a hotbed for fraudulent accounts | Layered defense with identity verification + RBAC + reporting | Ensuring reliability |
An interactive demo that recreates the real experience. You can try three scenarios: the user app, identity verification and the operations console.
The full journey: recommendations → profile → like → match → real-time chat.
A reassuring flow: document selection → upload → automated review → verified badge.
KPI dashboard, report moderation, billing revenue and staff permission management.