Reduce repetitive human review without giving up terminology control, privacy, or quality discipline

Pangeanic's Automatic Post-Editing workflows are designed for translation companies, multilingual content teams, and public-sector language departments that need stronger machine translation output while keeping control over terminology, review thresholds, and operational delivery.

Automatic post-editing is most valuable when it operates inside a controlled translation workflow. For organizations managing translation memories, glossaries, recurring documentation, and multilingual publishing at scale, the objective is not generic fluency. It is better output with less avoidable human correction work.

See the BYD AUTO JAPAN case, or review MTQE docs.

Lower post-editing effort in repeat workflows

Useful for LSPs handling technical, legal, product, or support content where TM leverage, terminology consistency, and edit reduction matter more than generic fluency claims.

Adapt output to internal terminology and style

Relevant for companies that own bilingual assets and want machine output to reflect approved wording, product naming, and multilingual publishing standards.

Keep privacy and infrastructure choices visible

For government teams, the decision is also about data handling, review accountability, throughput, and where the workflow runs.

Use prior translations, estimate quality, verify terminology

Pangeanic's APE is an adaptive translation workflow. The system uses customer reference material, retrieves relevant prior examples, evaluates output quality, and checks terminology and style before deciding what should still be reviewed by a human.

This is why APE is especially valuable in terminology-sensitive, repeatable, operational content. It is not a universal fix. It is a controlled way to improve the parts of multilingual production where consistency, throughput, and review discipline matter most.

• Use TMX, CSV, TSV, or approved bilingual assets
• Retrieve relevant prior translations for alignment
• Apply quality estimation before delivery
• Run verification checks on terminology and fluency
• Escalate questionable output to human review

Ingest

Bring in bilingual assets, TMs, glossaries, style preferences, or client-approved wording.

Adapt

Use retrieval and adaptation logic to reflect the client's existing language assets.

Estimate

Score quality so human review focuses on lower-confidence segments.

Verify

Check terminology, style, and output behavior before publishing or routing to linguists.

• Can the workflow use existing translation assets?
• Can quality be classified before human review?
• Can terminology and style remain auditable?
• Can the workflow fit into repeated delivery processes?
• Can review effort be concentrated where risk is higher?

When translation operations already work with approved terminology, recurring documentation, and established review teams, the main gain is operational efficiency with control. APE reduces avoidable correction work in production.

Can this run in a controlled workflow?

• Can language assets remain isolated per client?
• Can the workflow support private deployment?
• How does APE sit alongside MT infrastructure?
• How are lower-confidence segments prioritized?
• Can the workflow integrate without breaking existing processes?

Public docs that support the story

Pangeanic's public documentation helps support a stronger APE narrative because machine translation and MTQE are already documented as operational services.

MT overview · MT API · MTQE overview

Technical documentation

Manuals, specifications, support articles, and product documentation with stable terminology and repeated structures.

Public-sector documentation

Administrative text, multilingual notices, forms, citizen-facing content, and internal documentation where consistency and privacy matter.

High-volume enterprise content

Knowledge bases, product updates, internal portals, customer support content, and multilingual publishing workflows with recurring structure.