AI-Powered Business Matching
How SerbLink transformed professional networking with intelligent AI matching
SerbLink needed to move beyond basic directory listings and connect diaspora businesses with meaningful partnerships. We built an AI-powered matching engine that understands industry context, business goals, and communication styles to surface the right connections.
What they faced
SerbLink had a growing user base of Serbian diaspora businesses but struggled with low engagement. Users signed up, created profiles, but rarely returned. The existing search relied on basic keyword matching and manual category filtering — users had to know exactly what they were looking for. Most business partnerships that formed happened through offline events, not the platform. SerbLink needed a way to proactively surface relevant connections and make the platform a daily destination.
What we built
We developed a multi-signal AI matching engine that goes far beyond keyword search. The system analyzes business profiles using NLP to understand industry context, service offerings, and growth goals. It combines this with behavioral signals — what profiles users view, which messages they send, and what content they engage with — to continuously refine recommendations. The matching algorithm uses embeddings to find non-obvious connections: a logistics company in Chicago might be matched with a food distributor in Belgrade based on complementary supply chain needs, even though neither would have searched for the other.
How we built it
Profile Intelligence Layer
Built an NLP pipeline that extracts structured data from free-text business profiles — industry classification, service taxonomy, geographic reach, and growth signals. This creates rich, queryable representations without requiring users to fill out lengthy forms.
Embedding-Based Matching
Generated vector embeddings for each business profile and implemented approximate nearest-neighbor search. This allows the system to find semantically similar businesses and, more importantly, complementary ones based on supply-demand relationships.
Behavioral Learning Loop
Implemented a feedback system that learns from user interactions. Every profile view, connection request, and message exchange feeds back into the recommendation model, improving match quality over time without manual tuning.
Mobile-First Real-Time Feed
Designed a personalized daily feed for the mobile app that surfaces 5-10 high-quality matches with clear explanations of why each connection is relevant. Push notifications for particularly strong matches drive daily engagement.
Impact delivered
- ✓ Match acceptance rate of 89%, up from 12% with the previous keyword-based system
- ✓ Daily active users increased 210% within three months of launch
- ✓ Over 1,400 verified business partnerships formed through the platform
- ✓ Average time-to-first-connection dropped from 14 days to 2 days
- ✓ User retention at 90 days improved from 18% to 61%
"The AI matching completely changed how our users experience the platform. People are finding business partners they never would have discovered on their own. It turned SerbLink from a directory into a living network."
Technologies used
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