A CTO rebuilt their company's AI translation pipeline to reduce costs and avoid vendor lock-in by integrating a unified API providing access to 184 AI models. They benchmarked multiple models for translation quality and cost, routing bulk, UI, and marketing copy translations to different models based on quality and price. They implemented caching to reduce API calls by 40%, streaming for long documents, batching for short strings, and continuous quality monitoring with human reviews. This architecture enabled rapid iteration, easy model swapping, and a 55% reduction in monthly translation costs while maintaining or improving translation quality.

Jun 14, 2026, 1:30 AM