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AI Localization & MTPE

AI Localization & Quality Automation

Enterprise AI localization combining domain LLMs, neural machine translation (NMT), terminology constraint filters, and professional human post-editing (MTPE).

Mutual NDA available · Structured multi-pass review and QA
AI Localization & Quality Automation
AI Localization & Quality Automation ISO 17100 QA standards

Project Preparation

The following information helps accurately assess scope, timelines, and quotation.

01

Source Files

Provide source documents or corpus packages (Word, Excel, XLIFF, JSON, Markdown, PDF).

02

Target Languages

Specify target language pairs and regional audience standards.

03

Purpose & Audience

Clarify use case (internal knowledge base, e-commerce, tech guides, publication).

04

Terminology & References

Provide translation memories (TMX), glossaries (TBX), or prompt constraint rules.

05

Format & Timeline

Confirm quality level (Light MTPE vs Full MTPE), file formats, and delivery schedule.

💡 Note: For high-volume projects, a 1,000-2,000 word pilot sample evaluates MT engine quality and PE effort.

AI + Human Post-Editing (MTPE) Workflow

Corpus pre-processing, engine alignment, human expert post-editing, and TM archival.

01
Stage 01

Parsing & Term Injection

Parse text structures, isolate code tags, and inject glossary terms into model prompts.

02
Stage 02

Engine Machine Translation

Execute high-throughput translation via domain LLMs and NMT while protecting variables.

03
Stage 03

Automated QA Validation

Run automated checks for missing placeholders, numbers, tag corruptions, and term locks.

04
Stage 04

Human Post-Editing (Full MTPE)

Domain linguists review sentence-by-sentence to eliminate machine tone and ensure fluency.

05
Stage 05

Private TM Asset Archival

Final post-edited segments are archived into customer translation memories.

Deliverables

  • Final formatted documents post-edited to human publication standards (Full MTPE)
  • Post-editing effort and edit distance analysis report
  • Updated private translation memories (TMX) and termbases (TBX)
  • Automated QA compliance and consistency logs

Prerequisites & Scope Notes

  • Post-Editing Tiers: Light MTPE focuses on accuracy; Full MTPE delivers native publication fluency
  • Source Text Quality: Garbled source text requires pre-translation cleaning to prevent MT errors
  • Data Privacy: Processed via enterprise zero-data-retention APIs; never used for public LLM training
  • DTP Formatting: Complex CAD drawings and multi-column manuals integrate with DTP engineering

AI Translation & MTPE Technical Sample

Demonstrating raw machine translation output vs specialized human post-editing refinement.

View All Samples →
AI Translation & MTPE Technical Sample EN ➔ ZH-CN
Source (EN - Complex Technical Spec)

"Ensure the fail-safe interlock triggers a controlled shutdown whenever the differential pressure transducer reports an out-of-spec reading across the manifold."

Full MTPE Target (ZH-CN - Post-Edited by Domain Specialist)

“务必确保:一旦压差变送器检测到歧管两端读数超出规格,故障安全联锁装置即刻触发受控停机。”

Raw MT (Draft Flaw) Full MTPE (Human Polish) Post-Editing Rationale
Literal: "Trigger controlled closing..." Controlled shutdown Industry standard: Converts awkward literal phrasing into established technical command
Literal: "Pressure transducer reports..." Differential pressure transmitter GB/T Instrument Terminology: Standardizes transducer to transmitter in fluid systems
Literal: "Across the main pipe everywhere" Across the manifold Fluid mechanics context: Accurate spatial engineering translation of manifold reading
Sample Overview Sample ID: AI-MTPE-01

Chemical Fluid Control System O&M Manual

Service: AI Translation Post-Editing (Full MTPE) · Domain: Process Engineering

1

Eliminating MT Syntactic Artifacts

Restructuring nested English clauses into clear engineering condition-action statements.

2

Domain Term Correction

Fixing generic LLM mistranslations of instrumentation, valves, and piping terms.

3

Productivity Acceleration

2.5x throughput gain over traditional workflows while preserving human publication quality.

FAQ

Frequently asked questions

Common questions on pricing, turnaround, confidentiality and file formats—contact us for anything else.

How do AI and human translation work together?
MT + post-editing (MTPE) + QA suits high-volume or time-sensitive content; marketing and legal content often needs full human translation or enhanced review.
Can you use our MT engine and terminology rules?
Yes—we can connect client engines and apply glossaries, do-not-translate lists and style guides during MTPE.
How much does AI Localization & Quality Automation cost?
Pricing depends on word/page count, language pair, subject matter, timeline and formatting. Send a sample or files—we respond within 24 hours with a detailed quote.
What factors affect translation pricing?
Key factors: language pair, content type (general/technical/legal), layout/DTP, certified or notarized delivery, glossary work, rush fees, and volume for ongoing programs.
How long does translation take?
Typical documents are planned at roughly 2,000–3,000 source words per day; website and software work is phased by module. We confirm milestones during scoping.
Can you handle urgent projects?
Yes. Rush jobs use additional linguist/reviewer capacity and priority scheduling. Share your deadline when submitting—we confirm feasibility and options.

Ready to Start Your Project?

Submit your requirements and files. Our consultant will provide a transparent quote and timeline within 24 hours.

Mutual NDA execution supported
Evaluation delivered within 24 hours
Transparent pricing & clear scope

Ready to discuss your AI Localization & Quality Automation project?

Submit your materials to receive a tailored assessment and quotation.

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