Social Content Discovery & Community Platform

Built a scalable social media platform combining Pinterest, Instagram, and blogging — supporting 1M+ users with NLP-powered content recommendations, intelligent discovery, and cross-platform web and mobile delivery.

Company Context

A social media platform combining the content formats of Pinterest, Instagram, and blogging — enabling users to create posts, guides, blogs, and event listings. Designed for content discovery and community building, requiring intelligent recommendation to surface relevant content across a growing library of user-generated material.

Engineering Environment

MySQL NLPGoogle Places APIFull StackSEOSocial PlatformContent Recommendation

What Our Scale Partnership Revealed

Building a social platform for 1M+ users from scratch requires infrastructure decisions at the architecture level — every data model choice, query pattern, and caching strategy affects whether the platform scales or collapses under load.
The platform needed intelligent content recommendation — not just chronological feeds, but personalized discovery that surfaces relevant content based on user behaviour and preferences.
Multiple content types (posts, guides, blogs, events) each with different structures and discovery patterns needed to coexist in a unified platform.
Cross-platform delivery (web and mobile) from day one meant the backend architecture needed to serve both without duplication.

Engineering Work

Designed and built the full platform architecture from scratch — database schema, API layer, content management system, and discovery infrastructure all built for 1M+ user scale from the start.
Implemented content recommendation system using MySQL NLP features — content analysed at write time, recommendation queries use full-text relevance scoring to surface content matching user interest patterns.
Integrated Google Places API for location-based content and event discovery.
Built dynamic SEO infrastructure — every piece of user-generated content generates optimized metadata for organic discovery.
Delivered web and mobile applications from the same API layer.

System Outcome

Platform live at 1M+ user scale — architecture held under production load.
Intelligent content recommendation driving engagement across all content types.
Location-based content discovery enabled via Google Places integration.
SEO infrastructure generating organic traffic to user-generated content.

Engineering Breakdown+

Scale Architecture: Designed the database schema with read-heavy social platform patterns in mind — denormalized feed tables, pre-computed aggregates for like/comment counts, and separate read replicas for content discovery queries. Write operations go to the primary; recommendation queries hit replicas.

NLP Recommendation: MySQL FULLTEXT indexes on content body and tag fields. At content creation, tags are extracted and stored. Recommendation queries use MATCH AGAINST with relevance scoring, filtered by the user's historical interaction patterns to weight content categories they engage with.

Scale Partnership

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