Case Study: Ariel Corporation improves machine translation quality with Argos Multilingual AI TM cleanup

Ariel boosts Spanish MT zero-error content from 39.8% to 60% with Argos Multilingual

Ariel Corporation, a global manufacturer of gas compressors, faced the challenge of improving its machine translation output to reduce post-editing costs and accelerate time-to-market. Their existing translation memory contained inconsistencies that hindered quality, and a manual cleanup was too costly. They partnered with their language services provider, Argos Multilingual, to utilize its AI-powered TM cleanup tool.

Argos Multilingual implemented a two-step solution: first cleaning the translation memory with AI to eliminate errors and inconsistencies, and then using the cleaned data to train custom machine translation engines. This strategy significantly improved translation quality, with 55% of content achieving a 0% error rate and Spanish MT error rates jumping from 39.8% to 60%. The results led to reduced localization costs and faster publishing of translated content.

Ariel Corporation