Quality Estimation

Availability: Enabled by default for new projects, opt-in for existing ones. Requires enabled machine/AI translation.

Quality Estimation (QE) lets an AI evaluator score every AI-produced translation with a confidence estimate between 0 and 1, together with a short reason. The score is stored with the translation and surfaced in the editor, so you immediately see which AI translations are trustworthy and which ones deserve a human look.

Only AI translations are scored (traditional machine translation is not).
Scoring works for translations produced by the automatic translation workflow as well as AI bulk actions and the AI assistant in the editor.
Scoring uses the same AI provider that produced the translation: with your own API key (OpenAI, Gemini, Mistral AI) the scoring runs on your key; with the built-in Locize AI it consumes AI tokens like any other Locize AI usage.

Enable Quality Estimation

New projects have Quality Estimation enabled by default (the built-in Locize AI works out of the box). For existing projects:

Open your Project settings.
Go to EDITOR, TM/MT/AI, ORDERING.
In Cat settings, enable Quality Estimation (the toggle is available once machine translation is enabled).

What you see in the editor

A per-segment confidence indicator on AI-translated segments.
A confidence percentage (with the evaluator's reason as tooltip) next to the quality info of the selected segment.
A "by AI: needs review" filter in the state filters, listing AI translations scoring below the needs-review threshold (0.7 by default).

Low-confidence proposals routed via the Review AI workflow show the confidence, the critique, and a one-click suggested revision directly on the pending review.

When an AI translation is edited by a human, re-translated, or replaced from translation memory, its confidence score is removed automatically. A score always describes exactly the text it was computed for.

Review AI workflow (auto-route low confidence to humans)

With the additional Review AI workflow setting, low-confidence AI translations are not saved silently. Instead they are routed into the review workflow as pending proposals:

Low-confidence AI translations (score below the threshold, or with a major issue found) become pending reviews, even in languages that don't have the regular review workflow enabled.
High-confidence AI translations are saved directly.
Routed proposals carry a critique: issue categories (accuracy, fluency, terminology, style) with severity and a short note. When the evaluator can clearly improve the translation, it also includes a suggested revision you can apply with one click.
If a language has the regular review workflow enabled, everything still goes through review as usual; Quality Estimation then simply enriches those proposals with score and critique.

This differs from the regular review workflow: the review workflow reviews everything in selected languages, while the Review AI workflow reviews selectively, based on confidence, across all languages.

Good to know

The needs-review threshold defaults to 0.7. (Via API, qualityEstimationEnabled also accepts a number between 0 and 1 to use a custom threshold.)
Scoring roughly doubles the AI calls of a translation run. On very large namespaces the backend caps scoring per language and saves the remaining translations unscored.
Quality Estimation complements the deterministic checks & issues, it does not replace them: broken placeholders or untranslated fragments are best caught by those checks.
Scores are editor metadata: they are not included in your published translation files.
A Styleguide and Glossary improve the evaluator's judgement the same way they improve translations.