Improve machine translation quality automatically with our AI-powered post-editing API. Reduce manual review time while maintaining linguistic accuracy.
Around 95% of LSPs use machine translation. However, reviewing and manually post-editing can be time-consuming. Automatic Post-Editing (APE) ensures MT outputs are refined and polished before human eyes review them, reducing post-editing effort and maintaining quality.
Automatic Post-Editing (APE) is an AI layer that enhances machine translation post-editing efficiency. It automatically resolves linguistic issues in MT output, providing high translation quality management and production-ready content for global enterprise pipelines.
APE seamlessly integrates into your existing translation workflow
Use Prompt Studio to create custom post-editing rules tailored to your content and style requirements.
Choose from a library of leading LLMs, including GPT-4o, Claude 3.5, and Gemini, to find the best engine for your specific language pair and domain.
Connect your prompt to any workflow template and process thousands of segments automatically.
Prompt Studio — Build and test your APE prompts in real-time
APE is powered by Custom.MT’s Prompt Studio and AI model library, giving you full control over how and when post-editing happens.
A good APE prompt includes:
Role — defines AI’s function (e.g., “You are a post-editor specialized in technical translations.”)
Context — describes input conditions (e.g., “Preserve tags and curly brackets {…}.”)
Task — clear editing goal (“Ensure correct grammar and British English terminology.”)
Rules — concise editing standards.
Protection conditions — safety nets to prevent over-editing.
Protection conditions — safety nets to prevent over-editing.
Role:
You are a post-editor specialized in safety instruction translations.
Context:
You work with the result of a machine translation from French into British English.
The text may contain hazard symbols, technical units, tags, or curly brackets. You must preserve them exactly as they appear.
Task:
Edit the English translation to ensure it is grammatically correct, clear, and consistent with British English technical
and safety terminology.
Rules:
- Preserve the exact meaning of all safety instructions.
- Convert measurement units into the SI system, using the value provided in the source text.
- If the source text contains text in curly brackets, reproduce it unchanged in the translation.
- Ensure British English spelling and style (e.g., “labour”, “organisation”).
Protection conditions:
- Preserve all tags, placeholders, symbols, and curly brackets unchanged.
- If no changes are needed, return the text exactly as received.
- If the input segment is empty, contains only symbols, or has no meaningful content, return it exactly as received.
- Do not add comments, explanations, or formatting.
- Do not hallucinate or introduce new content.
- Never request additional input or clarifications.
- Input = one sentence → Output = one sentence.
Source segment in French:
{source_text}
Translated segment in British English:
{text}Once tested, APE prompts can be linked to any workflow template or CAT tool integration inside Custom.MT.
They run automatically across projects — ensuring consistent output without additional human touchpoints.
Seamlessly integrate APE into your existing translation workflows via REST API
Works with leading TMS platforms including Trados, memoQ, XTM, and more
Process thousands of segments simultaneously with enterprise-grade security.
Build tailored post-editing pipelines that match your exact quality requirements
APE automatically corrects machine translation output using AI-driven prompts. Unlike manual post-editing, it scales instantly across thousands of segments and ensures consistent grammar, terminology, and style — without human effort.
Yes. Custom.MT gives you full control over the editing logic through Prompt Studio. You define the rules, tone, terminology, and constraints; the system executes them automatically, exactly as configured.
For most production workflows, GPT-4o offers the best balance of speed, cost, and tag stability. For more complex or stylistic tasks, teams often compare results with GPT-5 or Claude 3.7/4 Sonnet. If you need broad multilingual style adaptation, Gemini 2.5 Pro is a strong choice.
Yes. Prompts include mandatory protection conditions that preserve tags, symbols, and curly brackets. For example, “{25 mg}” remains unchanged in the output.
APE works across many scenarios:
All processing happens in EU-based infrastructure (AWS Frankfurt) with no data retention. Nothing is stored after the job is completed, making APE suitable for privacy-sensitive and regulated industries.
Yes. Once your prompt is ready, you can connect it to any template in the Console and run it across Trados, memoQ, XTM, Smartcat, and other connected systems. One prompt can scale across thousands of projects.
Yes. Custom.MT Console is designed for long-term flexibility. As new LLM generations are released, you can reuse the same prompt structure, compare output across models, and upgrade your workflows without vendor lock-in.