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Case Study

SuperIntro

An AI-powered relationship and networking platform that automatically matches users, assigns them to events, and enables meaningful conversations.

Role

Full-Stack Engineer / Technical Lead

Period

Jan 2025 – Jun 2025

Location

Remote · US-based startup

Stack

Next.js, TypeScript, Node.js

The Challenge

Turn varied user information into relevant relationship recommendations while coordinating delivery across frontend, backend, and design disciplines.

Engineering Approach

The platform combined a RAG matching pipeline with LangChain, LangGraph, and Azure OpenAI, backed by a TypeScript product stack, real-time communication, scheduled generation, and multi-environment cloud deployment.

What I Worked On

• Led sprint planning, architecture, code review, and technical delivery within a 14-member team
• Designed RAG matching pipelines with LangChain, LangGraph, and Azure OpenAI
• Built real-time communication and in-app notifications with WebSockets
• Containerized APIs and clients for multi-environment GCP Cloud Run deployment
• Automated weekly match generation and implemented Stripe subscriptions

Tech Stack

Next.jsTypeScriptNode.jsMongoDBLangChainLangGraphAzure OpenAIWebSocketsStripeGCP

Impact

→ ~30% improvement in match relevance
→ 400+ users
→ Five recommendations per user
→ 14-member delivery team

Related Expertise

Backend engineering ↗AI systems ↗Node.js consulting ↗

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