AI Efficiency Curve
ISO 18587-certified MTPE services featuring:
▶ DeepL/Google MT engine preprocessing + proprietary domain adaptation
▶ Three-tier LQA verification (grammar/terminology/style)
▶ Dynamic terminology database with real-time TM synchronization
◼ 50+ language pairs ◼ 8,000 words/hour throughput ◼ 40-60% cost reduction
Intelligent Post-Editing Solutions
Revolutionizing MT+PE Workflows
Smart Preprocessing
◈ Domain adaptation training
◈ Sensitive data filtration
◈ Format auto-parsing
◈ Sensitive data filtration
◈ Format auto-parsing
Expert Post-Editing
◈ Industry terminology specialists
◈ Style guide compliance
◈ Cultural localization
◈ Style guide compliance
◈ Cultural localization
Quality Firewall
◈ Xbench automated QA
◈ Three-tier verification
◈ Real-time dashboard
◈ Three-tier verification
◈ Real-time dashboard
Dynamic Optimization
◈ Adaptive TM updates
◈ Error pattern learning
◈ Engine self-tuning
◈ Error pattern learning
◈ Engine self-tuning
FAQ
How is sensitive data handled?
On-premises MT deployment + ISO 27001 compliance
How to measure cost savings?
PEeffort coefficient reports with visualized efficiency metrics
Supported file formats?
XML/JSON/Markdown/Office (+30 formats) with style retention
MTPE Workflow
Human-AI Collaborative Process
Intelligent Corpus Cleaning
Format standardization/Sensitive data filtering/Terminology alignment
Multi-engine Collaboration
DeepL + Proprietary engine + Domain-tuned models
Tiered Editing
PE1 basic editing → PE2 professional polishing → LQA validation
◼ IoT device manual ◼ Volume: 850k characters
◼ Terminology consistency: 99.2% ◼ Delivery time reduced by 60%
◼ E-commerce UGC content ◼ Daily processing: 32k entries
◼ Sentiment accuracy: 93% ◼ Cost reduction: 55%
Real-time TM Dashboard
EN→JA
“neural machine translation” → “ニューラル機械翻訳”
New term added
“neural machine translation” → “ニューラル機械翻訳”
New term added
ZH→DE
“云计算” → “Cloud Computing”
Reused (23rd time)
“云计算” → “Cloud Computing”
Reused (23rd time)
1,234
Today’s updates
86%
TM match rate
Expert Q&A
Key Differences Between MTPE and Traditional Translation?
Technical Comparison:
- Workflow: Traditional translation uses linear “Translate → Proofread → Review” process, while MTPE implements closed-loop “MT Pre-translation → Tiered Editing → Smart QA” workflow
- Quality Assurance: Implements LISA QA 3.1 model with 52 evaluation metrics across 12 dimensions
- Efficiency Gains: Our data shows in technical documentation processing:
Metric Traditional MTPE Daily Throughput 2,500 words 8,000 words Term Consistency 92% 99.5% Cost/1k Words $100 $45
How is Data Security Ensured?
Five-Layer Protection System:
- Physical Isolation: Dedicated server clusters for financial/medical data
- Encrypted Transmission: TLS 1.3+SM4 dual-layer encryption
- Dynamic Masking: Auto-detection and replacement for 15 PII types (IDs/bank cards)
- Access Control: RBAC model with granular permissions
- Audit Trail: Complete operation logging with blockchain verification
How to Select Optimal MT Engine?
Engine Selection Framework:
Based on 1,200+ project analyses, we recommend:
Content Type Analysis:
- Technical Docs → DeepL + Custom Engine
- Marketing Content → Google MT + GPT-4 Fine-tuning
- Asian Languages → NiuTrans + CTRANS
Quality Requirements:
- SAE J2450 Compliance Levels:
- Basic (75-84) → Single Engine
- Professional (85-94) → Dual Engine Fusion
- Publishing Grade (95+) → Triple Engine Consensus
Global MTPE Partner
5M+ Words Processed