Accelerate global growth with intelligent translation memory technology

Translation memory is a database that stores previously translated text segments alongside their source language equivalents. When you upload new content for translation, the system automatically searches for matching or similar segments from previous projects.

If it finds exact matches, those translations can be reused immediately. For similar content, translators receive suggestions they can adapt, significantly speeding up the process whilst maintaining consistency.

Most companies see cost reductions of 20-40% when using translation memory effectively. The savings depend on how much content you repeat across projects and languages.

For example, if you regularly translate product descriptions, marketing materials, or technical documentation with similar content, you’ll see substantial savings. The more you use the system, the more valuable your translation memory database becomes.

Yes, translation memory works with virtually any text-based content including websites, marketing materials, technical documentation, legal documents, and software interfaces. The technology is particularly effective for content with recurring elements like product descriptions, user manuals, or standardised messaging.

Some content types benefit more than others. Highly creative or unique content may have fewer matches, whilst technical documentation or product catalogues typically show excellent reuse rates.

Translation memory doesn’t compromise quality because it only suggests previously approved translations. Every segment in the database has been reviewed and approved by qualified translators or editors.

When translators receive suggestions, they can accept, modify, or reject them based on context. This human oversight ensures quality whilst dramatically reducing the time needed to translate similar content.

XTM’s translation memory includes powerful terminology management features that let you update translations across your entire database. When you change how a term should be translated, the system can identify all instances and help you update them consistently.

This global update capability is crucial for maintaining brand consistency, especially when you rebrand products or refine your messaging strategy across markets.

You’ll begin seeing benefits immediately, even with a new translation memory database. As you complete your first projects, the system starts building your database of approved translations.

Most companies notice significant efficiency gains after translating 50,000-100,000 words. The benefits compound over time as your translation memory grows, making each subsequent project faster and more cost-effective.

Absolutely. XTM’s translation memory system is designed for collaboration. Multiple translators can access the same database simultaneously, ensuring consistency across team members and projects.

The system tracks who made changes and when, providing full audit trails. Project managers can also set permissions to control who can add or modify translation memory entries.

XTM implements enterprise-grade security measures to protect your translation memory data. This includes encrypted data transmission, secure server infrastructure, and regular security audits.

Your translation memory database is your intellectual property, and we treat it with the highest security standards. You maintain full control over your data and can export it at any time.

XTM supports over 50 file formats including Microsoft Office documents, Adobe files, HTML, XML, JSON, and many content management system formats. The platform automatically extracts translatable text whilst preserving formatting.

This broad format support means you can use translation memory benefits across all your content types without worrying about compatibility issues or manual file preparation.

Fuzzy matching identifies segments that are similar but not identical to previous translations. The system calculates similarity percentages, typically showing matches above 75% similarity.

For example, if you previously translated “Save your document” and encounter “Save your file”, the system recognises the similarity and suggests the previous translation as a starting point. Translators can then adapt the suggestion for the new context, saving time whilst ensuring accuracy.