Building a Modern Translation Management System: A Comprehensive Case Study

Introduction

Managing translations in modern web applications can be challenging. While there are many commercial Translation Management Systems (TMS) available, they often come with significant costs, vendor lock-in, and limitations in customization. This article series introduces a production-ready, open-source alternative that combines modern web technologies with AI capabilities to create a powerful, cost-effective translation management solution.

Project Goals

• Create a production-grade translation management system using open-source technologies

• Achieve high performance through modern caching strategies and optimizations

• Provide an excellent developer experience with automation tools and TypeScript integration

• Maintain minimal operational costs using serverless and efficient infrastructure

• Leverage AI capabilities for translation assistance while maintaining human oversight

• Support collaborative translation workflows for teams of any size

Why Another TMS?

Many organizations face common challenges with translation management:

• Commercial solutions can be prohibitively expensive, especially for growing projects

• Professional translation services often cost thousands of dollars per language

• Existing tools often lack deep integration with modern web frameworks

• Developer experience and automation are frequently afterthoughts

• Custom requirements often can't be met with off-the-shelf solutions

• AI translation capabilities are either missing or poorly integrated

This project addresses these challenges through several innovative approaches:

Cost-Effective Translation with AI

By leveraging Large Language Models for translations, this system provides high-quality translations at a fraction of the cost of professional translation services. Early results show that AI-generated translations are often on par with or even superior to traditional translations, while being an order of magnitude cheaper.

Developer-First Approach

The system includes unique developer features that significantly reduce manual work:

• Automatic mapping of translation keys to pages, eliminating tedious documentation

• Automated key detection and management

• Built-in TypeScript support for type-safe translations

• Seamless integration with modern web development workflows

Minimal Operational Costs

The entire system is designed to be incredibly cost-efficient:

• Currently running at $0/month using serverless infrastructure

• Scales efficiently with usage

• No expensive dedicated servers required

• Optimized AI usage to minimize costs

What to Expect from This Series

This article series will provide a detailed walkthrough of implementing a complete translation management system. All features discussed are already implemented and running in production, making this a practical, real-world guide rather than a theoretical exploration.

Each article will focus on a specific aspect of the system, from basic setup to advanced features like AI integration and collaborative workflows. Whether you're looking to implement the entire system or just specific features, you'll find practical, tested solutions that you can adapt to your needs.

Part 1: Introduction and Technical Foundation

• Overview of the TMS and its purpose

• Technical stack and hosting infrastructure

• Vercel deployment

• fly.io hosting

• MongoDB Atlas Serverless

• Core technologies

• Next.js framework

• React.js library

• TypeScript implementation

• REST API

• GraphQL integration

• Payload CMS

• Internationalization basics

• react-intl integration

• FormattedMessages component usage

• Understanding locales (e.g., en-GB format and common confusion points)

Part 2: Core Translation Infrastructure

• UIString collection in Payload CMS

• Structure and purpose

• Description/context fields for translator guidance

• Translation key management

• Automatic page-to-key mapping script

• Import structure analysis (both static and dynamic)

• Key-to-page relationship tracking

• GraphQL implementation

• Loading translations via GraphQL

• Code generation process

• Request validation and typing

• Caching strategy

• Next.js ISR implementation

• Performance optimizations

Part 3: Automation and Developer Tools

• Frontend scanning automation

• Script for detecting new UIString keys

• Automatic creation in local Payload CMS

• Default translation handling

• Frontend default translations (planned feature)

• Integration with FormattedMessage

• Deployment workflow

• Translation upload script (local to production/staging)

• Integration with existing import/export system

Part 4: AI-Powered Translation Features

• Bulk translation capabilities

• ChatGPT integration

• Alternative LLM support

• ChatGPT function calling

• Structured object handling

• Custom Payload CMS translation field

• Multiple translation suggestions (5 options)

• Selection interface

• AI configuration

• Settings Global for ChatGPT prompts

• Prompt placeholder system

• AI model selection interface

• Custom endpoints for translation services

• Bulk translation endpoint

• Suggestion translation endpoint

Part 5: Translation Management Dashboard

• Translation progress tracking

• UIString translation ratio display

• Untranslated string management

• Links to pending translations

• Bulk operations

• Edit overview

• Translation initiation

• Export functionality

• Draft system

• Basic draft functionality

• Enhanced UI for drafts (planned feature)

• Quality control

• AI-powered translation quality checking (planned feature)

• Typo detection

• Low-quality translation flagging

Part 6: Collaboration and Access Control

• Editor collaboration tools

• Editor notes integration

• Collaborative translation workflow

• Role-Based Access Control (RBAC)

• Editor role definition

• Translation manager permissions

• Draft approval workflows

• UI enhancements

• Default text display while editing other locales

• Context preservation