Case study
Game localization across 100+ titles and 7 languages.
A games localization program needed more than 100 titles localized across 7 languages without breaking in-game layouts, where translated text rarely matches the source length.
100+ - 7 - 70,000 words
110,000+
verified language specialists
Language specialist network
300+
languages across active service lines
4,500+
dialects and regional variants
110+
rare and indigenous language pairs
1,000+
projects delivered since 2015
Measured outcomes
Game localization at title scale
Project overview
What landed, and what made it hard.
A games localization program needed more than 100 titles localized across 7 languages, delivered through top-100 LSP partners.
Delivery snapshot
Game localization at title scale
- Client
- confidential game publishers (via top-100 LSP partners)
- Service
- Game localization
- Languages
- 7 languages
- Volume
- 70,000 words across 100+ titles
Why this mattered
Outcome before process.
Game text lives inside fixed UI: buttons, menus, and dialogue boxes that break when translated strings run longer or shorter than the source.
The problem to solve
Why the work was difficult, and what MoniSa changed in-flight.
Each language expands or contracts text differently, so a menu label that fits in English can overflow in one language and look empty in another.
The challenge
The problem to solve
Each language expands or contracts text differently, so a menu label that fits in English can overflow in one language and look empty in another.
Across 100+ titles and 7 languages, keeping every string inside its in-game space required per-title attention, not a single global rule.
Operating response
What MoniSa changed
MoniSa localized each title with its in-game constraints in view, adjusting length and phrasing so translated text held its place in the interface.
- Length-aware translationLinguists wrote to the space a string had, while preserving source meaning.
- Per-title handlingEach title was treated on its own terms instead of forcing one rule across the catalogue.
- Tone for playDialogue and UI kept a natural game voice in each language rather than reading as literal translation.
Results
Measured outcomes from this engagement.
More than 100 titles were localized across 7 languages, with in-game text expansion and contraction managed per title.
| Titles | 100+ |
|---|---|
| Languages | 7 |
| Volume | 70,000 words |
| Quality | Independently reviewed |
| Focus | In-game text fit and player voice |
Selection logic
What protected the result.
Game localization rewards UI-aware linguists who write to the space, beyond translators who render meaning.
Why the fit was real
Why the fit was real
Game localization rewards UI-aware linguists who write to the space, beyond translators who render meaning.
What decided the result
What decided the result
Per-title length management is what kept menus, buttons, and dialogue intact across 7 languages.
What buyers can reuse
What buyers can reuse
- Game localization succeeds or fails on whether translated text fits the interface it lives in.
- Per-title length management beat a single global rule across a 100+ title catalogue.
- The evidence keeps clients confidential and attributes the metrics only to this engagement.
Continue from this proof
Useful comparisons for the same problem.
Use these links to compare the case with the matching service, buyer guide, and language coverage.
Mapped context
Service and buyer context
Languages named
Examples referenced in the engagement.
- Brazilian Portuguese
- Japanese
- Korean
- South Asian languages
More proof
Related proof
Compare this case with Streaming localization across rare languages and Six years of app localization to judge whether the operating pattern fits your brief.
case evidence
Nearest proof pattern.
These related cases keep the next click close to the same kind of work.
Localization servicesA continuous five-month healthcare SaaS localization program held level on quality.
Healthcare SaaS localization
The challenge. A healthcare SaaS platform needed Hindi localization as a continuous program where quality slips carry real cost.
What we did. MoniSa ran the account with a steady reviewer team and a fixed glossary, treating month-over-month consistency as the deliverable.
The result. A 100K-word Hindi program delivered across five continuous months with quality issues stayed inside the agreed review path.
Translation servicesFour concurrent localization programs run through one partner without dropping any.
Four concurrent localization programs
Problem. A global e-commerce platform needed marketing QC, e-commerce, recall-compliance, and HR localization running at once.
Action. MoniSa sourced each program to its own quality bar and held all four to a common reliability standard across rolling batches.
Result. Over a million words and 350+ hours of QC across four programs, sustained over 19+ batches with continuity controls.
AI data servicesA 150-specialist on-site deployment in Tokyo for direct model-refinement work.
On-site linguist deployment
Problem. An AI company needed Japanese-language specialists on-site, working directly with its engineering team.
Action. MoniSa deployed 150 specialists in Tokyo and settled into a steady on-site production team.
Result. On-site collaboration moved model refinement faster than a remote workflow.
Buyer questions
Ask the questions weak vendors avoid.
Short answers for buyers checking fit, coverage, quality method, and next-step readiness.
What was delivered on this engagement?
Titles: 100+. Languages: 7. Volume: 70,000 words
What control kept the work stable?
Per-title length management is what kept menus, buttons, and dialogue intact across 7 languages.
Where should similar work go next?
Use Localization services for the delivery model, Media localization buyer guide for buyer-side evaluation, and the contact page for a scoped brief.
Similar brief
Send the constraint behind the metric.
A useful follow-up to a case study names the language mix, review model, deadline, and what proof your buyer team needs before approval.
Production-ready brief
01Closest matching challenge from this case02Language pair, dialect, and script coverage03Volume, cadence, or hours to deliver04Reviewer model and acceptance criteria05Security or platform constraints06Proof needed for stakeholder approval