Multilingual Support System Using Large Language Models: Architecture, Workflow, and Implementation Plan

Current Situation and Issues

The international logistics system currently supports nine languages with tens of thousands of terms per language, leading to translation complexity, inconsistency, and high maintenance cost.

Analysis of Causes

Manual translation processes are costly and inefficient; the emergence of GPT offers more accurate, lower‑cost translation, but still falls short of professional standards.

Plan Objectives

Real‑time multilingual support using large models.

Improve translation quality through model‑learned historical data.

Accelerate term updates via a "Term Butler" feature.

Enhance user participation and feedback loops.

Reduce reliance on external translation vendors.

Increase system intelligence with behavior‑driven recommendations.

Enable continuous learning and optimization.

Implementation Steps

4.1 Build an International Terminology Library

Consolidate existing terms into a standardized multilingual glossary for reuse across systems.

4.2 Inline Term Editing

Users can select terms on the front‑end, edit them in a pop‑up window, submit for approval, and have changes applied automatically.

4.3 Architecture

Leverage the company’s large‑model platform (GPT, Yanxi) for custom translation of new language packs and terms, embed professional term libraries, enforce language‑specific rules, and integrate automated correction mechanisms.

Deploy translated packages to cloud storage; automatic versioning ensures front‑end applications always fetch the latest language pack, with fallback to cached versions for offline resilience.

Expected Outcomes

5.1 Productivity Gains

Automation can save roughly two person‑days per month per iteration by reducing manual term corrections and deployment cycles.

5.2 Quality Improvements

A unified terminology library ensures consistent, accurate translations across all logistics systems, minimizing user confusion and enhancing professional presentation.

Conclusion and Future Planning

The multilingual term library is underway; ongoing refinement will further streamline internationalization, automate updates, and provide a seamless, user‑driven translation experience.