Machine translation (MT)

Machine translation enables organizations to translate large volumes of content quickly and cost-effectively. Early MT systems relied on rule-based or statistical models, analyzing language patterns to predict translations. Modern systems use neural machine translation (NMT), which employs deep-learning networks to understand sentence structure, semantics and tone.

MT workflows typically begin with source-content preparation, followed by automated translation through a trained engine. Human linguists then review and refine the output – a process known as Machine translation post-editing (MTPE / post-editing). This combination of automation and expert review allows businesses to manage multilingual content efficiently and maintain quality at scale. Machine translation supports a wide range of applications – from technical documentation and website localization to multilingual customer support and enterprise communication. When integrated with content-management and translation management systems, it enables continuous localization and faster time-to-market.

RWS delivers enterprise-grade MT through Language Weaver, a secure, neural-machine-translation platform built for scalability and domain adaptation.

Language Weaver combines advanced AI models with industry-specific customization, enabling organizations to train engines that reflect their brand voice and terminology. RWS blends human linguistic expertise with intelligent automation, ensuring every translation is accurate, secure and culturally appropriate. Through integrations with Trados and other enterprise platforms, RWS helps organizations achieve continuous localization and multilingual content delivery at scale.