Braid: Unleashing the true value of your localization assets

Over the last four decades, Alpha CRC has provided clients around the world with expert localization services, including translation and transcreation, full content creation, and multilingual voiceover production.  

Now, in engaging with the future of localization and how technology is changing the landscape of the translation industry, we have developed Braid, an AI-powered tool which helps improve efficiency and accuracy in translation, while augmenting productivity in workflows.

Whether glossaries, translation memories, or style guides, localization experts have worked hard to develop a range of assets that define your company’s approach to translation. But are you using those assets to their best effect? Braid is designed to help businesses leverage their existing translation assets (or build up new ones), unleashing their value in much more exciting and interesting ways than just policing translation output.

How Braid works

Step 1: Fuzzy match enhancement – unlocking translation memory value

Braid works by scanning segments to find fuzzy matches. These are segments that are similar but not identical to something that has been previously translated. When Braid finds a fuzzy match, it intelligently updates the existing translation to match the new source text. Instead of starting from scratch or manually editing lengthy segments, the AI:

• Preserves as much of your original translation as possible, only changing what’s necessary based on the differences in the old and new source content
• Maintains your translation style and terminology choices
• Retains any formatting and keeps tags in their correct positions

Step 2: Smart translation generation – brand-aligned output from the start

For segments without fuzzy matches, Braid creates first drafts using prompts tailored to your guidelines or the specifics of the project. It leverages your localization assets by using:

• Custom prompts tailored to your brand (integrating style guides etc.)
• Your terminology database entries
• Language correction rules, such as Regex (regular expression) replacements
• Special formatting preservation throughout the segments

Using Braid for translation generation ensures that your machine output is in line with your brand – no characterless, middle-of-the-road localization here. Instead, you can rest assured knowing that your customers are engaging with your authentic brand voice.

While Braid is a segment-based tool, there is also a ‘Context’ feature, which sends the preceding and following segments to AI for more accurate results.

How Braid works best: implementing TMs and TBs

Translation Memory (TM) best practices

Braid can do much more than routine tasks, and can be as creative as the prompts it’s been given. We use top LLMs (OpenAI and Anthropic models) under its hood, and their creativity is measured by the user’s input.

Braid uses the provided resources (TM fuzzies, TB hits, prompts, etc) and applies them to each segment individually. This means that each translation Braid works on and receives linguist approval becomes a foundation for future enhancements. For this reason, it’s essential that any Translation Memories which are used to teach the AI are maintained and updated regularly.

With Braid, your localization assets, such as translation memories and glossaries, become significantly more valuable. Well-maintained resources are now more important than ever. Here are some key considerations:

• Regular cleanup: Remove outdated or incorrect translations, as the AI will perpetuate these mistakes if not regularly cleared of obsolete content
• Consistency is key: Well-maintained TMs will give a better indication of tone and style. Longer, context-rich segments provide better training data for Braid – simply put, there is more consistent material for it to learn from, and the AI can more easily pick up any style preferences and desired idiosyncrasies

Term Base (TB) management

Likewise, Braid needs help with managing Term Bases in order to provide the best service. Linguists include industry-specific terms, client preferences, and style choices in the Term Bases, as well as adding detailed notes about when and how to use specific terms, and keeping terminology current with feedback and industry changes.

How AI handles Regex replacements also needs to be considered. Regex (regular expression) replacements are automatic text corrections applied after AI translation, such as number formatting and spacing rules that apply to some languages. These rules can be customized for any specific requirements, ensuring consistency across large projects while reducing post-editing time.

Optimized workflow: Braid and human linguists in partnership

In order to optimize Braid’s performance, linguists work with the tool through each phase of the workflow. Their tasks include:

Preparation phase

During the preparation phase, linguists maintain the Translation Memory by reviewing and updating existing translations, while organizing the Terminology Base to ensure terminology remains current and comprehensive. They also create project prompts by developing specific instructions tailored to different clients or text types, and set up regex rules by configuring language-specific corrections.

During translation

Throughout the translation process, linguists review AI suggestions and validate fuzzy match enhancements while adjusting and refining prompts based on AI output quality. They continuously add new terms discovered during translation and remain vigilant for common AI mistakes so that prompts and regex rules can be improved accordingly.

Quality control

At the quality control stage, linguists focus on context, nuance, and cultural adaptation during post-editing, while checking consistency by verifying terminology application across the project. They ensure the AI has followed the prompt instructions and document successful patterns and areas for improvement for future reference.

Why use Braid: in a nutshell

By performing the more routine and repetitive aspects of the translation process, Braid allows linguists to focus on the parts which require more intellectual and creative scrutiny, and more individual handling.

Braid’s key actions:

• Handles repetitive fuzzy match updates
• Provides intelligent first drafts
• Applies terminology consistently
• Maintains formatting integrity
• Speeds up initial translation phases

A productive partnership

Braid handles the mechanical aspects of translation while linguists focus on the intellectual and creative challenges that make translation an art. Linguists’ knowledge, cultural understanding, and linguistic intuition remain a crucial part of the translation process, supported by intelligent automation.

The future of translation is collaborative, and by building a partnership between linguists and AI, Alpha CRC can deliver higher-quality translations more efficiently while maintaining the human touch that makes translation truly excellent.