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Bridging localization and development teams for consistent translations 
A global enterprise providing business management tools across 12+ countries for 15 million customers.
ChallengeGitLab repositories store the client's up-to-date multilingual content. However, when the client would make changes to their content, the updates weren't reflected in vendors' Translation Memories (TMs). This led to significant bottlenecks in the localization process and discrepancies between vendors. It forced the client to make extensive manual editing of translations. As a result, the localization process became time-consuming and prone to errors.
SolutionOur team at localize.io designed and implemented a pipeline that synchronizes the client's multiple GitLab repositories and Translation Memory (TM) in the Crowdin Translation Management System (TMS).
How it works
1
Translations Extraction:All approved translated content is exported from GitLab repositories.
2
Translation Memory Compilation:All the content is processed into one dataset.
3
Sync with Crowdin:Course content is uploaded to Crowdin for translation, and translated content is downloaded.
4
Format Transformation:TM is converted into a compatible format for TMS.
5
Upload to Crowdin:TM is transferred to Crowdin, making the localization process more efficient and translations consistent.
The pipeline automatically runs when GitLab repositories are updated.
Do you have questions about the pipeline?
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Workload summary
15 languages:English, Arabic, Spanish (Mexico), French, Japanese, Indonesian, Italian, Malay, Polish, Portuguese (Brazil), Thai, Turkish, Ukrainian, Vietnamese, Chinese Simplified, Chinese Traditional
2.1 million translation records processed
Results
Automated process
Continuous synchronization between GitLab repositories and TMS maintains translation consistency.
Consolidated Data
All language resources are merged into a single, deduplicated Translation Memory.
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