AIPE Workflow

AIPE is Glodom’s human-AI collaborative translation workflow. After file upload and language asset integration, T-agent performs machine translation, while R-agent identifies quality issues such as terminology, grammar, and style inconsistencies. Translators use E-agent for issue correction and complete post-editing in Trados, followed by R-agent validation to ensure delivery quality.

Machine Translation → AI Review → Human Post-Editing → AI Validation

This workflow combines AI efficiency with human expertise, enabling faster delivery while maintaining translation quality.

Quality Assurance

AIPE adopts a dual-layer quality model: AI-powered screening + expert human review.
Powered by Glodom’s proprietary QA tools and LLM technology, R-agent automatically checks terminology consistency, numbers, units, tags, and translation fluency, with issues traceable at paragraph or sentence level.Experienced linguists perform post-editing in professional CAT tools such as Trados, supported by AI-generated reports. Translation memories and terminology databases ensure consistency, while version tracking enables full process traceability.

QA Agent

QA Agent is Glodom’s intelligent quality review agent within the AIPE workflow. 

Combining traditional rule-based QA engines with large language model capabilities, QA Agent goes beyond conventional keyword-based checks. It identifies issues such as spelling errors, numerical inconsistencies, and missing tags, while also evaluating semantic accuracy, logical consistency, and domain-specific requirements. QA Agent can detect translations that are technically correct but lack naturalness or contextual appropriateness.

Advantages

Compared with fully human translation, AIPE reduces costs and shortens delivery cycles, especially for fast-changing content such as technical documents, game updates, and app releases.

Through AI review combined with expert post-editing, AIPE delivers both speed and quality. Translation memories, terminology databases, and QA rules continuously accumulate, enabling reusable language assets and increasingly consistent delivery.