AI-powered translation platform

An AI-powered translation platform that knows your terminology

Generic AI translation tools see one sentence at a time. LanguageOps gives the model your translation memory, approved terms, style guide and reference files, then scores every segment with automated LQA before a human decides what ships.

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  • Frontier models, your choice per job
  • 80+ file formats round-tripped
  • Human review built in
Why context matters

Machine translation is fluent. Fluent is not the same as correct.

Automatic translation software has become very good at producing natural sentences. What it still gets wrong is what your organisation has already decided: the product name that must not be translated, the approved legal phrasing, the formal register for Germany, the term your support team uses. An AI translation platform fixes that by supplying the decisions, not just the text.

  • Your memory and terms go in first

    Before a segment is translated, LanguageOps retrieves relevant translation-memory matches, termbase entries and project instructions, so the model starts from what you have already approved.

  • Every segment is scored

    Rule-based QA checks tags, numbers and terminology. Cross-lingual LQA classifies errors by type and severity, so reviewers start with the segments most likely to be wrong.

  • People stay accountable

    Translators and reviewers edit AI output in a full CAT editor. Their corrections update memory and terminology, so the next job starts closer to right.

How the AI translation pipeline works

From source file to approved translation

  1. Prepare

    Engineer the file

    Upload Word, InDesign, JSON, XLIFF, spreadsheets, subtitles or scanned PDFs. LanguageOps extracts translatable text and protects tags, code and layout for the return trip.

  2. Research

    Build context

    Optional research mode studies the subject, product and audience, and suggests terminology before translation starts, which helps most with new clients and specialist domains.

  3. Translate

    Pre-translate with the right model

    Choose from the supported frontier models per project, or compare their output on a sample first. Memory matches, terms and style rules are applied to every segment.

  4. Verify

    QA, LQA and human review

    Automated checks and LQA scoring flag risky segments. Linguists review, edit and approve in the editor, then export to the original format.

What the platform includes

AI translation tools for the whole job, not just the sentence

Every paid plan includes the full suite. Plans differ in capacity, seats and support, never in features.

  • Model choice and comparison

    Run the same sample through several models and compare the output side by side before committing a large project to one engine.

  • Terminology enforcement

    Approved and forbidden terms are shown to the model and to the linguist, and QA flags segments where the approved term was not used.

  • Style guides and brand voice

    Formality, tone, audience and house style rules travel with the project and apply to AI and human work alike.

  • Privacy mode

    Pre-translate with a local model using your approved memories, terms and reference files, so sensitive content does not leave your infrastructure.

  • Video, audio and live speech

    Transcribe, subtitle and dub video, or run live multilingual captions for meetings and events, from the same account.

  • Connectors and API

    Pull work from Phrase, Lokalise, WordPress and GitHub, or create jobs over the REST API and MCP server from your own systems.

Transparent pricing

AI capacity is included in every plan

Professional starts at £250 a month with 200,000 words and 5 million AI tokens included. Top-up tokens are available at any time, with no forced upgrade.

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What an AI-powered translation platform actually does

“AI translation” covers everything from a free browser translator to an enterprise localisation suite. They mostly draw on the same families of models. What differs is everything around the model.

Type of tool Typical examples Good for Where it falls short
Free automatic translators Google Translate, DeepL, Microsoft Translator Understanding a message, quick drafts, low-risk text No memory of your past decisions, limited terminology control, formatting often lost, no quality measurement
General AI assistants ChatGPT, Claude, Gemini Rewriting, explaining, short creative adaptation Inconsistent across long or repeated content, manual copy-paste, no review workflow or audit trail
Localisation platforms (TMS) Phrase, Lokalise, Smartling, Crowdin Continuous software and content localisation at scale AI often metered in separate pools or sold as add-ons, and pricing is quote-based. See our TMS pricing comparison
AI translation platform LanguageOps Business content that has to be right: documents, product, marketing, regulated text Needs a short setup: memory, terms and style guide, which the platform helps you build

An AI-powered translation platform combines three things that free tools and chat assistants do not:

  1. Retrieval of your language assets. Translation memory, termbases, style guides and reference files are supplied to the model for each segment. This is what turns a fluent translation into your translation.
  2. File engineering. Real content arrives as DOCX, IDML, XLIFF, JSON, spreadsheets, subtitles and PDFs. The platform extracts only translatable text, protects tags and code, and rebuilds the file afterwards. See supported file formats.
  3. Measurement and review. Automated QA and linguistic quality assessment (LQA) score the output so a human reviewer can focus on the segments that need it. See consistency, QA and LQA.

How accurate is AI translation?

Accuracy claims for automatic translation software are rarely comparable, because they depend on the language pair, the subject and how “accurate” is measured. Independent research gives a more honest picture:

  • Google Translate varies widely by language. A 2021 UCLA-led study in the Journal of General Internal Medicine had native speakers review 400 Google-translated emergency-department instructions. Overall meaning was retained in 82.5% of translations: 94% for Spanish, 90% Tagalog, 82.5% Korean, 81.7% Chinese, 67.5% Farsi and 55% Armenian (Taira et al., 2021).
  • Large language models are not automatically better. A 2024 comparison of ChatGPT and Google Translate on patient instructions found ChatGPT mistranslated 3.8% of Spanish sentences against Google’s 18.1%, but 24.2% of Vietnamese sentences against Google’s 10.6% (Rao et al., 2024).

Two practical conclusions follow for business translation:

  • Test on your own content and languages. A model that performs well for Spanish marketing copy may not for Vietnamese product documentation. LanguageOps lets you run the same sample through several models and compare the results before committing a project.
  • Measure every job, not just the pilot. Quality drifts with new content types, new reviewers and new model versions. Scoring each segment with QA and LQA gives you evidence on every delivery, not a one-off benchmark.

You can see worked AI translation examples, with typical errors and how review corrects them, for more than 40 languages in our AI translation by language guides.

How to choose an AI translation tool

Use this checklist when you compare AI translation tools, platforms or services:

  • Context: Does the tool apply your translation memory, termbase and style guide to every segment, or only offer a glossary?
  • Formats: Can it return your DOCX, IDML, JSON or XLIFF with formatting, tags and placeholders intact?
  • Quality evidence: Does it score output with QA and LQA, and can you see which segments are risky?
  • Human review: Can translators and reviewers edit, comment and approve in the same place, with history?
  • Learning: Do corrections flow back into memory and terminology automatically?
  • Model choice: Are you locked into one engine, or can you choose and compare models per job?
  • Data control: Where is content processed, and is there a local or private option for sensitive material?
  • Cost model: Is AI usage included and predictable, or billed in separate pools and add-ons?

AI translation software or AI translation services?

Some teams want to run translation themselves. Others want the job done. LanguageOps supports both:

  • Platform: your team, or your freelancers, use the editor, AI models, QA and connectors directly. See pricing.
  • Managed service: we scope the work, prepare difficult files, run AI with your assets, coordinate professional reviewers and deliver approved files. See managed translation services.

You can also combine them: start with a managed project, then run later work yourself once memories and terminology are established.

Frequently asked questions

AI-powered translation, explained

What is AI-powered translation?
AI-powered translation uses machine learning models, today mostly neural machine translation engines and large language models, to translate text automatically. The difference between tools is less about the model and more about what surrounds it: whether it uses your terminology and past translations, whether it handles your file formats, and whether it measures quality before delivery.
How accurate is Google Translate?
It depends heavily on the language and content. In a 2021 study of 400 translated emergency-department instructions published in the Journal of General Internal Medicine, Google Translate kept the overall meaning in 82.5% of cases, ranging from 94% for Spanish to 55% for Armenian. The authors concluded it should not be relied on for patient instructions. For business content, accuracy also drops when a tool cannot see your terminology or context.
Is AI translation better than Google Translate?
Large language models can use far more context than a sentence-by-sentence translator, which helps with terminology, tone and ambiguous phrases. They are not uniformly better: a 2024 study comparing ChatGPT with Google Translate on patient instructions found ChatGPT made fewer errors in Spanish but more in Vietnamese. That is why LanguageOps lets you compare models on your own content and scores the output with LQA rather than trusting any single engine.
What is the best AI translation tool for business?
For a quick one-off sentence, a free translator is fine. For business content that is published, sold or regulated, choose a platform that applies your translation memory and terminology, preserves file formatting, measures quality with QA and LQA, supports human review, and gives you control over where data is processed.
Can AI translation replace human translators?
For low-risk, high-volume content, AI with automated QA can be enough. For legal, medical, marketing and customer-facing content, the most reliable approach is AI pre-translation followed by human review of the segments LQA flags, with corrections fed back into memory and terminology.
Do you offer AI translation services as well as software?
Yes. You can run the platform yourself, or send the job to our managed translation service. We prepare the files, run AI translation with your assets, coordinate professional reviewers and deliver finished files.
Where is my content processed?
LanguageOps runs on EU-based servers. For sensitive work, privacy mode runs pre-translation on a local model so content stays on your infrastructure. See our data processing agreement, or talk to us about specific requirements.

Test AI translation on your own content

Bring a real file, your glossary and a target language. We will show you model output, LQA scores and the review workflow side by side.

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