Workflow
Create a context-aware localization
A good localization is more than a correct translation.
Localizethat combines AI language intelligence with the company context relevant to your content, so the first localized version starts with more than just the source words.
This guide explains what happens when you select Localize and how different kinds of context influence the result.
What makes a localization context-aware?
Modern AI already has strong language capability.
What it usually does not know automatically is how your company has decided to communicate.
Localizethat uses both at the same time: AI language intelligence helps understand the source, meaning and target language, while company context helps guide how that meaning should be expressed for your company.
Localizethat
Localization intelligence
Context-aware localization
Start with the source
The source is the content Localizethat should preserve and localize.
A good source should be the version your team actually wants target markets to work from.
“External reviewers are free and do not need a Localizethat account.”
The source contains the meaning that needs to be preserved.
Company context then helps determine how that meaning should be expressed in the target language.
Content type adds another layer of context
You never pick a content type as a step. Localizethat detects what kind of content you added and applies the matching company rules.
The same company may communicate differently in a press release and a social post.
Content type helps Localizethat apply sensible defaults for the communication format without requiring the user to explain those expectations every time.
“External reviewers are free and do not need a Localizethat account.”
“Need a local expert to review the translation? Invite them directly. External reviewers are free and don’t need a Localizethat account.”
Same message. Different content context.
Illustrative example
Localizethat applies the relevant company context
When you select Localize, Localizethat can use the company context available for that localization.
Not every context type needs to affect every sentence.
The goal is to use the context that is relevant to the content and target market.
Brand voice
Guides how the company should sound.
Terminology
Guides which words and product terms should be used.
Approved claims
Protects statements where precision matters.
Market rules
Guides market-specific communication decisions.
Translation memory
Provides previously approved translations when useful.
Previous approved language
Provides examples of language the company has already reviewed and accepted.
Relevant context is applied automatically when it is available.
See how different context changes the result
One consistent message, shown with different company context applied.
“AI can translate your words. It doesn’t know your company.”
“AI can translate your words. It doesn’t know your company.”
The source is already clear and can be preserved almost exactly.
“AI already understands the language. What it doesn’t know is how your company has decided to communicate.”
Brand voice can influence how directly or editorially the same idea is expressed.
“company context”
“prompt library”
“brand database”
“AI knowledge base”
Terminology can keep the product vocabulary consistent even when several alternatives would be linguistically understandable.
- “The intelligence is complex. The workflow shouldn’t be.”
- “Your local teams should review. Not rewrite.”
- “Translate once. Review locally. Remember everything.”
Previous approved language gives Localizethat examples of the style and messaging the company already accepts.
Illustrative examples of how context can guide wording.
Some context protects meaning, not just style
Company context is not only about tone.
Some decisions exist to stop important meaning from changing during localization.
“Start with 10 free credits.”
Preserve
10 free credits
Do not infer
Unlimited free localization
10 free translations
All usage is free
An AI model can understand all of these phrases, but they do not mean the same thing.
Approved claims give Localizethat a controlled reference for what the company has actually approved.
Market context can change how the same message is expressed
Localization is not always about reproducing the same sentence structure in another language.
A company may have specific communication rules for a market.
Use a restrained, factual tone. Avoid unnecessary superlatives and overly promotional calls to action.
Example only
“Transform the way your team works across every market.”
“Manage localization more consistently across markets.”
Both express a related product benefit, but the second follows the example market rule more closely.
Market rules should reflect decisions your company has actually made. Do not use cultural stereotypes as rules.
Previous decisions can reduce repeated work
When your company has already reviewed and approved a translation or terminology decision, Localizethat can make that information available again.
English: “External reviewers are free.”
Swedish: “Externa granskare är kostnadsfria.”
“External reviewers are free and do not need a Localizethat account.”
Known from previous approval
“External reviewers are free.”
New information to localize
“and do not need a Localizethat account.”
The previous translation provides useful context without forcing Localizethat to treat the whole new sentence as an exact match.
The result should still be reviewed
Context-aware does not mean automatically correct.
AI language intelligence and company context can create a stronger starting point, but human judgement still matters.
Localizethat can use review signals to help show where attention may be useful.
Review signals help prioritize attention. They are not a guarantee of translation accuracy.
You should not need to manage the complexity yourself
The intelligence is complex.
The workflow shouldn’t be.
Your team should not have to rebuild prompts, remember every terminology decision or manually paste company instructions into an AI tool for every localization.
01
Add your content
02
Choose languages
03
Localize
Localizethat handles the relevant company context behind the workflow.
What happens after localization?
Each target language moves into its own review workflow.
- Review the localized content
- Leave comments
- Suggest edits
- Approve segments
- Invite a local reviewer
- Approve the target language
- Finalize approved localization
Approved decisions can then become reusable context for future work.
How to get better results from company context
01
Keep context specific.
Use Brand voice for communication style, Glossary for terminology and Approved claims for statements that need protection.
02
Use approved examples.
Examples your company has actually reviewed are more useful than large volumes of uncurated copy.
03
Do not turn every preference into a global rule.
Some decisions only belong to one campaign, market or sentence.
04
Review the first versions carefully.
Good human feedback creates better company knowledge for future localization.
05
Maintain your context.
Terminology, claims and communication rules change. Keep the company context aligned with current company decisions.
Put your company context to work.
Create a localization with the language intelligence of modern AI and the company knowledge Localizethat keeps available around it.
Related guides
Create your first localization
Walk through content type, source, languages and the first localized version.
How Brand voice works
Define how your company should sound before language decisions are made.
How Terminology & Glossary work
Keep product and company vocabulary consistent across markets.
How Approved claims work
Protect statements where precision matters during localization.
How Market rules work
Capture communication decisions that apply to a specific market.
Review localization with local teams
Send each language to the right reviewer and track review progress.