Game & Document Localization · AI CAT Platform

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Translation & Review

TM · TB · RAG · QA on a single grid
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Workbench — game_strings_v2.xlsx
v1.3.2
Projects
game_strings_v2v1
ui_labels
cutscene_script
TM
ON · 2.5M seg
Pre-translated 74%
Glossary
ON · 15K
Style
Score 88
KOEN
Flash
TM pre-translation
Style check
#
Source (KO)
Target (EN)
Match
1
아레나에 오신 것을 환영합니다
Welcome to the arena
TM 100%
2
모든 파워업을 수집하세요
Collect all power-ups
TM 88%
3
최후의 보스를 물리치세요
Defeat the final bo
AI
4
레벨 클리어!
Context
TM
TB
RAG
100% Full Match
보스를 물리치세요
Defeat the boss
85%
모든 보스를 처치하세요
Defeat all bosses
72%
보스 스테이지 클리어
Beat the boss stage
1M+
TM segments
15K+
Glossary entries
3
Frontier AI models
99.9%
Service availability (SLA)
Workbench

One Workbench,
the whole translate-and-review pipeline

TM · Glossary · RAG · Style Guide, connected in real time
Enterprise-grade AI CAT tool

01

Real-time TM matching,
then pre-translate in bulk

Surfaces Full, Fuzzy and Partial matches from your translation memory as you move through the sheet, then pre-translates every segment that clears your match threshold.

100% / 102% match Fuzzy 60%+ Partial Match Bulk pre-translation
TM pre-translation results
Fuzzy 70%+
100%
Welcome to the arena
Auto-applied
88%
Collect all power-ups
Needs review
72%
Beat the boss stage
Fuzzy match
247
Auto-applied
89
Needs review
77
Untranslated
02

Style guides built from your own edits,
then enforced across the file

Generate style rules from finished translations, or diff your translation and review columns to learn the patterns your reviewers actually apply. Every cell that breaks a rule is flagged, and fixes go in with one click.

Auto-generated rules Consistency check Flagged violations One-click bulk fixes
Style check results
88
Score
PASS 214 WARN 18 ERR 6
Inconsistent register
6 cells mix imperative and descriptive voice
Terminology inconsistency
18 terms translated ad hoc instead of the glossary entry
Missing translations
No untranslated cells ✓
03

RAG semantic search for
context and similar translation patterns

Upload reference documents or past translations — embeddings are generated for you. Search them semantically on the source or target side, or inject the match straight into the cell you are working on, so translation and review stay grounded in your own material.

Source/Target embedding Semantic search Auto context injection Similarity scoring
RAG search results
Semantic 50%+ match
"boss skill"
skill_description.xlsx 84.1%
Source최종 보스의 페이즈 3단계 스킬 중 하나이며 전체 범위에 대해 즉사기를 시전합니다.
TargetOne of the final boss's Phase 3 skills, casting an instant-kill move across the entire area.
style_guide_en.pdf 56.4%
…boss fights run three phases; at each transition use "enter Phase N", never "go into"…
Live lookup as you move between cells
Translation sheet RAG · 384 tokens of related context
04

Solving the MTPE (AIPE) problem

After post-editing, 14–30% of incorrect MT segments went uncorrected.

Another 6% of correct output was edited into a new error.

Minder et al. (2026) · MT post-editing study
What MTPE keeps costing you
NTurn
Errors you read past
Every segment scanned
Terminology and style drift
Blocked at translation time
Every cell checked by hand
One consistency check, applied everywhere
Glossary-aware batches TM 102% zero-edit reuse Every-segment scan Fewer cells to review
Cut review time, raise quality
2,480 segments

TM, glossary and style guide wired into every batch

Glossary 1,204 · 0 errors
TM 102% × 312 · no edit
Style guide 1,873

Style and pattern scans enforce consistency

Style scan 47 → Bulk fix
Pattern scan 23 → Bulk fix
RAG Context lookup, not keywords
Left to review 2,480 → 70
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