1.5M+ User Platform Infrastructure
Scaling Backend, Search & Personalization — Backend architecture and CRM development for a large-scale artist social platform, scaled from roughly 400K to 1.5M+ users with GraphQL, search, and AI-driven personalization.
What we were solving for
An artist social platform needed to grow from ~400K to 1.5M+ users without breaking API latency, search, or reliability — while still shipping new engagement features.
How we built it
GraphQL API optimization
Query tuning, pagination, and compound indexing cut response times from 5–6s to 1–2s.
Elasticsearch for search
Search offloaded from the primary database for speed at scale.
AI-driven recommendations
A content feed personalization system built on user engagement behavior.
Automation & scheduling
Node.js and Python pipelines to keep content workflows running.
Where it landed
Scaled from ~400K to 1.5M+ users while keeping the platform stable.
Cut GraphQL response times by roughly 70%, from 5–6s to 1–2s.
Shipped AI-personalized feeds on multi-region Kubernetes infrastructure in production.
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