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Case Study

Own product

Redictionary (WordBrain)

An AI-powered English-Korean vocabulary learning service combining structured dictionary generation, Redis caching, TTS audio, and quizzes.

A product we planned, launched, and operate ourselves. Read these as evidence of technical range and operating practice.

Project Overview

Redictionary turns English word searches into structured learning content. A NestJS API generates dictionary entries through structured OpenAI output, caches results in RedisJSON, creates pronunciation audio with Google Cloud Text-to-Speech, and serves quiz sessions, search history, and a React/Vite web app from an Nx monorepo.

Product screens

Searched word list and learning history screen
Searched word list and learning history screen
Structured dictionary entry generated by the LLM pipeline
Structured dictionary entry generated by the LLM pipeline
Vocabulary quiz list screen
Vocabulary quiz list screen
Quiz session screen
Quiz session screen
Quiz result with answer tracking
Quiz result with answer tracking

Key Challenges

  • Stabilizing LLM output as product data with a strict dictionary schema
  • Reducing generation cost and latency through RedisJSON caching
  • Avoiding duplicate pronunciation audio generation with hashed storage keys
  • Managing web, backend, mobile, and shared types in one Nx workspace

Key Outcomes

  • Built a full-stack vocabulary service with React, NestJS, Redis, OpenAI, and Google Cloud
  • Implemented structured dictionary generation, regeneration, and UI rendering flows
  • Added TTS pronunciation audio through Cloud Storage signed URLs
  • Created quiz lists, quiz sessions, answer tracking, and guest learning flows

Technologies

NxTypeScriptReactViteNestJSRedisJSONOpenAI APIGoogle Cloud TTSExpoDocker