AI Translation
Correct grammar does not mean your translation is production-ready: how to unit-test your text
This post is aimed at developers and people new to localisation who might be tempted to think an LLM’s output is perfect. At LanguageOps we have automated …
Council Translation: How Multi-Model Consensus Beats Single-Engine Output
Every machine translation engine has blind spots. DeepL struggles with certain idioms. Google Translate sometimes loses register. LLMs occasionally hallucinate. …
Cross-Lingual QA: Catching Errors Without Reading the Target Language
Translation quality assurance has a staffing problem. Finding reviewers who are native speakers of the target language, fluent in the source language, and …
Beyond DeepL: Why LLM Translation Changes Everything
DeepL is good. So is Google Translate. So is Microsoft Translator. The neural machine translation revolution of the mid-2010s genuinely improved translation …
The Post-MT Enhancement Pipeline Your Competitors Don't Have
Machine translation output in 2026 is good. It’s not good enough. Raw MT from DeepL, Google, or any major engine produces text that’s usually …
Context-Aware Translation: Why Surrounding Segments Matter
Translation tools divide content into segments—usually sentences. Each segment gets translated independently. Segment 47 is processed without awareness of …