Feasibility analysis
Before recommending post-editing, we review a sample, the content type, machine output quality, the text’s purpose, and its exposure level. If AI isn’t a solid base, we’ll tell you.
Initial diagnosisblarlo helps businesses, ecommerce brands, product teams, support, technical documentation, marketing, and international organizations turn machine translations into reviewed, consistent texts ready for real-world use.
MTPE post-editing combines the speed of machine translation with the judgment of professional linguists who fix meaning errors, align terminology, improve fluency, refine tone, and validate whether the text is suitable for publishing, support, internal documentation, or customer communication.
Post-editing—also known as MTPE (Machine Translation Post-Editing)—is the process of reviewing and correcting a machine-generated translation so the result is more accurate, natural, consistent, and fit for the content’s purpose.
Not every text is a good candidate for post-editing. Before we start, we assess machine output quality, content complexity, risk, channel, volume, deadline, and how exposed the text will be. This helps us avoid using AI where it doesn’t make sense and match the review level to the quality your business actually needs.
Machine translation post-editing for high-volume, recurring, technical, digital, or documentation content.
Light review for comprehension and internal use, or full post-editing for customer-facing, publishable, or higher-impact content.
Use of glossaries, translation memories, style guidelines, terminology review, and linguistic quality control.
Upfront diagnosis to choose between machine translation, MTPE post-editing, or professional human translation.
Each project is managed with a workflow designed to leverage machine translation efficiency and add the human review needed based on risk, channel, and the expected quality level.
Before recommending post-editing, we review a sample, the content type, machine output quality, the text’s purpose, and its exposure level. If AI isn’t a solid base, we’ll tell you.
Initial diagnosisWe define the right level: light review for comprehension, internal use, or low risk; full review when content must be published, sent to customers, or meet a quality level closer to human translation.
Quality levelA linguist reviews meaning, omissions, false friends, tone, grammar, fluency, terminology, and consistency to prevent invisible errors that machine translation can leave behind.
Human controlWe organize files, languages, deliveries, priorities, and tracking so multilingual projects maintain speed, order, traceability, and consistency across batches.
ScalabilityWe apply approved terminology, product names, brand preferences, translation memories, and style guidelines to reduce inconsistencies and improve quality in recurring projects.
ConsistencyWe review critical segments, formatting, consistency, terminology, figures, and proper names, working with corporate, technical, or commercial documentation under strict security and confidentiality standards.
Quality and securityPost-editing lets you scale multilingual content more efficiently than human translation from scratch and more safely than machine translation without professional review.
Shorter turnaround times for high-volume projects, many languages, or frequent updates.
A better balance of cost, speed, and quality when content doesn’t require full human translation from the start.
Fewer critical AI errors in meaning, terminology, tone, figures, omissions, consistency, or naturalness.
Greater consistency across catalogs, help centers, technical documentation, software, internal content, and recurring materials.
The ability to decide—based on clear criteria—which content can go through MTPE and which should move to professional translation.
Machine translation can produce fluent text that looks correct but contains errors in meaning, terminology, context, or tone. Post-editing reduces that risk before content reaches customers, users, or internal teams.
Invisible AI errors: natural-sounding sentences that change the original meaning or remove important nuance.
Inconsistent terminology across products, categories, manuals, interfaces, spec sheets, or support documentation.
Unnatural or overly literal text that reduces trust, conversion, and clarity for the end user.
Omissions, ambiguities, formatting issues, misinterpreted figures, or mishandled proper names.
Using AI for content that isn’t a good MTPE candidate, such as critical legal texts, creative claims, or high-exposure brand messaging.
Post-editing works especially well when there’s volume, structure, repetition, or a need to balance quality and efficiency. We adapt the review level to the content’s end use.
Product pages, attributes, categories, descriptions, FAQs, metadata, and recurring commercial content where scale and consistency are key.
High volumeHelp articles, support documentation, knowledge bases, user guides, and living content that’s updated frequently.
Recurring contentManuals, spec sheets, instructions, product documentation, maintenance, safety, and structured technical content.
Technical terminologyNewsletters, informational content, recurring campaigns, enablement materials, and commercial texts where tone and naturalness must be reviewed.
Style reviewInterfaces, system messages, onboarding, product documentation, release notes, help centers, and functional digital product content.
Efficient localizationInformational documentation, product communications, internal materials, support, and content where terminology must be checked with extra care.
Terminology accuracyTechnical, medical, scientific, or educational texts that can benefit from AI if the machine output is viable and human review is rigorous.
Specialist reviewCourses, internal manuals, policies, communications, onboarding, and training materials for multilingual teams.
Internal usePost-editing quality depends on choosing the right content, setting up the right workflow, and reviewing against clear criteria. That’s why we use a process that combines diagnosis, human review, and final quality control.
We review source language, target language, volume, format, industry, end use, content visibility, and the quality of the initial machine translation.
We define whether machine translation, light post-editing, full post-editing, or professional translation from scratch is the best option.
We align glossaries, translation memories, style instructions, approved terminology, quality priorities, and acceptance criteria.
The post-editor reviews meaning, accuracy, terminology, grammar, fluency, consistency, tone, formatting, and suitability for the end use.
We check critical segments, consistency, figures, proper names, formatting, and agreed requirements before delivering the content.
For recurring projects, we update glossaries, memories, review criteria, and workflow learnings to improve quality and efficiency.
The difference is turning machine output into content reviewed with human judgment, terminology control, QA, and a clear decision on the quality level you actually need.
| blarlo | Machine translation only |
|---|---|
| Upfront diagnosis to confirm whether content is suitable for MTPE or requires professional translation. | Direct AI use without assessing risk, output quality, the text’s purpose, or content exposure. |
| Light or full post-editing depending on goal, channel, budget, deadline, and expected quality level. | Same treatment for all content, even though not all texts carry the same impact or risk. |
| Human review of meaning, tone, terminology, consistency, fluency, figures, proper names, and formatting. | Fluent text but not necessarily correct, with potential errors that are hard to spot without professional review. |
| Glossaries, memories, style guidelines, linguistic QA, and centralized management for recurring projects. | Inconsistent processes as languages, files, teams, versions, or updates increase. |
| Honest recommendation between machine translation, MTPE, or human translation to avoid unnecessary costs and risks. | Lower upfront cost, but higher risk of rework, inconsistencies, brand errors, or comprehension issues. |
The cost of post-editing depends on word count, language pair, machine translation quality, content complexity, format, urgency, glossaries, QA level, and review depth. Send us the file or a sample and we’ll assess whether the content is suitable for MTPE.
| Project type | Recommended for | What we assess | Quote |
|---|---|---|---|
| Light post-editing | Internal content, operational documentation, comprehension texts, multilingual drafts, and low-exposure materials. | AI quality, volume, language, deadline, format, minimum correction level, and the content’s purpose. | Request a quote |
| Full post-editing | Customer-facing content, ecommerce, published help centers, technical documentation, digital products, and corporate materials. | Review of meaning, terminology, style, fluency, consistency, QA, glossary use, formatting, and expected quality level. | Request a quote |
| Web and ecommerce post-editing | Product pages, categories, landing pages, marketplaces, FAQs, emails, metadata, and recurring commercial content. | Volume, structure, commercial tone, keywords, formatting, recurrence, consistency, and localization needs. | Request a quote |
| Recurring MTPE project | Businesses with frequent translations, large batches, multiple languages, living documentation, or continuous workflows. | Frequency, memories, glossaries, review criteria, assigned teams, QA, response times, and formats. | Request a quote |
| Standard translation | AI Translation with Human Post-Editing | Sworn translation | |
|---|---|---|---|
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0,06€/word | 0,03€/word | 0,10€/word |
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0,06€/word | 0,03€/word | 0,10€/word |
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0,06€/word | 0,03€/word | 0,10€/word |
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0,06€/word | 0,03€/word | 0,10€/word |
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0,06€/word | 0,03€/word | 0,10€/word |
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0,06€/word | 0,03€/word | 0,10€/word |
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0,06€/word | 0,03€/word | 0,10€/word |
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0,08€/word | 0,04€/word | 0,12€/word |
Machine translation is useful when volume and speed matter most. Post-editing adds human review so you can publish or use content more safely. When the text is legally sensitive, creative, strategic, ambiguous, or high-impact for your reputation, we recommend considering professional translation from scratch.
If your project combines different quality levels, urgency, or exposure, blarlo can help you choose the right workflow within the same service ecosystem.
Professional translations in every language your business needs: English, French, German, Portuguese, Italian, Turkish, Catalan, Basque, Swedish, Dutch, Polish, Romanian, Arabic, Russian, Chinese, Japanese... By working with major international clients, we can offer you the best quality and the most competitive rates on the market.
Access our main specialized divisions directly based on your specific project parameters, data formats, or distribution channels.
Clear answers to help you decide when to use machine translation with human review, what level of post-editing you need, and how to prepare your project.
MTPE post-editing is the human review of a machine translation. A professional post-editor corrects errors in meaning, terminology, grammar, tone, consistency, and naturalness so the final text is more reliable and fit for its intended use.
Machine translation produces a first draft using AI. Post-editing adds a layer of human review to correct errors, improve quality, validate terminology, and adapt the text to the context, channel, and end reader.
Light post-editing aims to make the text understandable and useful for internal or low-risk content. Full post-editing reviews meaning, style, terminology, and fluency in greater depth for publishable content or customer-facing materials.
It depends on machine translation quality, the content type, and the review level. In some projects, full post-editing can come very close to human translation; for creative texts, critical legal content, or highly strategic messaging, translating from scratch may be the better option.
It’s a good fit when there’s volume, tight deadlines, structured or recurring content, and a need to improve machine output before publishing it, integrating it into a website, using it in support, or sending it to customers.
It’s not always recommended for critical legal texts, creative claims, premium campaigns, highly persuasive copy, documentation with high ambiguity, or content where an error could have reputational, contractual, or regulatory impact.
Yes. blarlo can manage recurring post-editing with glossaries, memories, review criteria, dedicated teams, linguistic QA, centralized tracking, and continuous workflow improvement.
Ideally, send the source language, target language, content type, volume, format, deadline, end use, exposure level, a sample of the machine translation output, and any available glossary, memory, or terminology instructions.
Beyond words, what truly matters is our clients’ experience. Here’s what people already working with Blarlo have to say.
I worked with the blarlo translation agency in Paris and was delighted with the result. The quality of the translations was exceptional, while the customer service was very caring and professional. I recommend blarlo to any individual or company seeking translation services in the city. Blarlo Paris is incredible!
We’ve contracted Blarlo’s services on several occasions and they’ve never let us down. They’re professional, efficient, and responsible with deadlines, all while offering very competitive prices. I have only positive things to say about this agency and I’ll definitely count on them again for future projects.
We contacted blarlo for an important translation project. The job itself was of a sensitive nature, from Basque into English and Spanish. They were aware of its importance throughout the entire process and provided helpful comments as well as a professional result. I was particularly impressed by the speed and quality.
Blarlo’s service was very efficient and professional at every step (from the RFQ to the end product: translating our research material from English into Dutch). They took control of the entire process, paying particular attention to our needs and delivering the translation on time. We are very happy with the results!
Tell us what content you need reviewed, which languages you work with, the project volume, whether you already have machine translation output, and the text’s end use. With that information, we can recommend light post-editing, full post-editing, or professional translation.