If you manage localisation at scale, you’re under constant pressure: more content to publish, tighter deadlines to meet, and stricter compliance to uphold. But here’s the reality: Not every piece of content needs the same level of review.
The real challenge is knowing when good enough is good enough and when only expert validation will do. That’s where the translation quality spectrum comes in. It helps you balance speed, cost, and accuracy without wasting effort — so you can scale up efficiently while keeping risk under control.
Machine translation (MT) plays a key role in this spectrum. Once the punchline of jokes — clunky, literal, and only useful for “getting the gist” — MT has improved dramatically with neural networks and large language models. Early MT was like the Swedish idiom: “Rise as a sun, fall as a pancake.” Impressive at first, but collapsing under nuance.
Today, the baseline quality of machine translation has improved dramatically. But MT alone isn’t the full story: It’s now part of a broader ecosystem that combines automation with expert refinement.
Each MT-based workflow builds on the previous one by adding increasing levels of human involvement (from quick post-editing to in-depth validation) to enhance accuracy, fluency, and cultural relevance. The result is a spectrum of quality options that can be tailored to the content type, audience, and business risk.
At the same time, achieving the best results means finding the right balance in the review process. Human expertise is what brings context, creativity, and quality assurance to the table; while AI helps reduce unnecessary manual work and streamline repetitive tasks. The goal isn’t perfection everywhere, but rather a smarter use of resources: applying human effort where it creates the greatest impact and ROI.
For global organisations, that’s both an opportunity and a challenge: you can localise more content than ever before, but what does “quality” actually mean now, and how much is the right amount to invest?
The translation quality spectrum: From MT to hybrid AI-human solutions
Localisation quality isn’t binary (“good” vs “bad”). It sits on a sliding scale of accuracy, fluency, and human involvement. And importantly: each department will use the entire spectrum depending on the content type, audience, and risk involved.
1. LanguageWire MT – Speed with intelligence
What it is: LanguageWire MT is a secure, enterprise-grade machine translation solution powered by advanced AI models. It combines Translation Memory (TM) and AI-powered Terminology to ensure consistency, accuracy, and contextual relevance across all your content — giving you instant, high-quality translations at scale.
Best for: Internal communication where speed and scalability matter more than tone or style.
Customer benefit: Share information instantly across languages with consistent terminology and contextual accuracy, without the time or cost of human review.
Examples across departments:
Marketing: Early campaign briefs or draft creative concepts for internal alignment.
Product & Engineering: Bug reports, early release notes, or technical updates shared across teams.
Customer Support: Translating chat logs or tickets for quick internal resolution.
Legal & Compliance: Understanding foreign-language documents for internal reference (not for official use).
2. Light post-editing – Clarity at low cost
What it is: A quick pass by a linguist to fix grammar and clarity.
Best for: Simple, functional content where style isn’t critical.
Customer benefit: Deliver clear, usable content fast — without overspending on polish.
Examples across departments:
Marketing: Campaign landing or event sign-up pages with straightforward copy.
Product/Engineering: Technical documentation for internal teams.
Customer Support: Self-service articles prioritising clarity.
Legal/Compliance: Internal HR updates or training materials.
3. Full post-editing (PEMT) – Reliable customer-facing quality
What it is: Machine translation combined with professional-level edits for precision, style, and linguistic quality. The result is natural, coherent content that closely resembles human translation.
Best for: Customer-facing content where clarity, accuracy, and brand consistency are essential.
Customer benefit: Achieve high-quality, brand-aligned translations faster and at a lower cost than traditional translation.
Examples across departments:
Marketing: Large volumes of product descriptions or campaign materials that need to reflect brand voice while maintaining speed and consistency.
Product/Engineering: Release notes or user documentation for customers.
Customer Support: Help centre content that shapes the customer experience.
Legal/Compliance: Internal compliance policies employees must follow.
4. Proofreading and polish – Protect your brand reputation
What it is: Proofreading is a professional review by a second linguist; a 4-eye principle process that provides a second set of expert eyes after translation or post-editing. Our native-speaker proofreaders correct spelling, punctuation, and grammar errors, ensuring clarity, accuracy, and fluency. For translated content, proofreading of translation also checks terminology, consistency, and tone against approved termbases and brand guidelines.
Best for: High-visibility content where precision, compliance, and brand perception matter. Ideal for regulated industries such as legal, healthcare, and finance, as well as marketing and technical communication that must be accurate and publication-ready.
Customer benefit: Proofreading helps you avoid costly misunderstandings, ensures terminology accuracy, and strengthens localisation; making sure your content is not just correct, but contextually appropriate and consistent in every language.
Examples across departments:
Marketing & Communications: Catch grammar errors and tone inconsistencies before campaigns go live. Maintain a strong brand voice across channels and markets.
Product & Technical Documentation: Ensure manuals, packaging, and documentation are accurate and compliant — especially in regulated industries.
HR, Legal & Compliance: Protect your brand with legally sound, internally consistent messaging across all regions.
Ecommerce & Retail: Avoid misprints on packaging and labels. Guarantee accurate, multilingual product information from descriptions to UX copy.
5. Expert / in-country validation – Minimise compliance risks
What it is: In-country review is an optional step in your translation workflow that brings your local experts into the process. These subject-matter specialists review and approve content before it’s published, ensuring it’s not only accurate but also culturally relevant, compliant with local regulations, and aligned with your brand voice.
Best for: Legal, regulatory, or safety-critical content — or any material that must meet local market requirements and resonate authentically with target audiences.
Customer benefit: Strengthen trust and reduce risk by combining professional translation with local expertise. In-country review ensures cultural relevance and that your content meets local market requirements.
Examples across departments:
Marketing: Local adaptation of campaigns and messaging to ensure cultural and linguistic resonance.
Product & Engineering: Verification of safety-critical manuals, packaging instructions, or installation guides to meet local regulations.
Customer Support: Review of escalation scripts and communication templates in highly regulated industries like healthcare or aviation.
Legal & Compliance: Local validation of clinical trial documentation, financial disclosures, and other regulatory filings before submission.
Learn how in-country review ensures cultural and regulatory accuracy.Factors shaping the right level of review
The right point on the spectrum depends on:
Content type: Regulatory filing vs informal blog.
Audience: Regulators, customers, or employees.
Business risk: What’s at stake if errors slip through?
Budget & deadlines: How much can you invest?
Workflow maturity: Can AI raise the baseline before humans step in?
The smartest organisations map content types to the spectrum ahead of time, so stakeholders understand why some texts need full human review while others do not.
But mapping alone isn’t enough, you also need a way to act on those decisions at scale. That’s where AI-powered quality assurance comes in. By raising the baseline of machine translation and guiding expert effort, AI ensures that human review happens only where it adds the most value.
How AI is raising the baseline
Artificial intelligence doesn’t replace expert review; it enhances it. By improving machine translation output and helping identify where human effort has the most impact, AI amplifies the variety of solutions that can cater to every level of the quality spectrum.
LanguageWire’s AI Quality Assurance combines two complementary technologies:
AI Quality Estimation (AIQE): Acts like a quality scanner. Every machine-translated segment receives a confidence score from 0–100. High-scoring segments can be “locked” and ready to go, while low-scoring ones are flagged for deeper review. The model detects areas that are more likely to contain linguistic inaccuracies, terminology issues, or stylistic inconsistencies; ensuring that expert editors focus on the segments that truly need refinement.
For teams who use Smart Editor, AIQE scores appear directly in the working environment, helping reviewers prioritise effort and avoid wasted checks. For enterprises with fully managed workflows, AIQE operates behind the scenes — guiding expert reviewers to focus only where it matters most.AI Editing (AIE): Functions like a built-in copy editor. It automatically improves grammar, fluency, and syntax in low-scored MT segments identified by AIQE, reducing post-editing effort even before experts step in. This means reviewers start with cleaner drafts, spend less time on basic corrections, and can focus on tone, nuance, and compliance.
Together, AIQE and AIE help organisations prioritise the right areas for review while raising the overall baseline of quality. Instead of treating all content equally, teams get sharper control: critical segments get the expert attention they deserve, while lower-risk content moves quickly through the pipeline with confidence.
Learn more about AI Quality AssuranceFrom raw output to excellence
Translation quality today is no longer about avoiding “bad MT.” It’s about knowing which level of quality fits the purpose — and having the right mix of people and technology to get there.
There is a spectrum of content — from low-stakes to high-stakes — and each department has different needs depending on content type, audience, and risk. The art is in balancing speed, cost, and accuracy without wasting effort.
Quality in localisation isn’t about chasing perfection everywhere. It’s about being strategic. By understanding the content and quality spectrum, organisations can:
Scale content production without creating bottlenecks.
Align departments on a shared definition of quality, reducing internal friction.
Reduce compliance risk by applying the right level of review where it matters most.
Prove ROI by matching effort and investment directly to business risk.
That’s why LanguageWire offers a full range of solutions to match the right quality to the right purpose.
From instant machine translations to ISO certified human quality output (and everything in between), our workflows are designed to deliver fit-for-purpose quality, adapt to your needs and scale with your ambitions.
AI-powered quality assurance plays a central role, amplifying the benefits of a hybrid AI tech and expert service approach: AIQE guides reviewer focus, while AIE raises the baseline of machine translations, so teams review already improved drafts. Combined with our expert linguists, secure infrastructure, and scalable technology, you get a flexible setup that connects people, processes, and platforms seamlessly.
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