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GenAI Translation Pipeline

LLM-powered translation system that cut turnaround time by 20% at Lingpad

March 2026

Key Highlights

20% reduction in client turnaround timeFlexible multi-provider LLM architectureClient-specific glossary and translation memory systemProduction-grade prompt engineering layer

Technologies Used

PythonDjangoPostgreSQLRedisLLM APIsPrompt EngineeringREST APIs

Led the end-to-end design and implementation of an LLM-powered translation pipeline for Lingpad's localization platform. Evaluated multiple LLM providers, built a flexible provider-switching architecture, and designed the prompt engineering layer. Also built a client-specific glossary and translation memory system that eliminated terminology inconsistencies. The system became a core product differentiator and directly contributed to a 20% reduction in client turnaround time.