W30 Product Update: Engine Suggestions learn from human edits

Localization Engine Suggestions now come from the corrections human reviewers make, not only from low AI-review scores.

When a reviewer edits a translation – whether in-house or through an external provider – the localization engine compares the change against what it first produced. When the same fix recurs across jobs, or a correction clearly sets a term, it proposes the glossary, instruction, or brand-voice edit behind it. Apply writes the change into the engine, and the next translation runs with the fix in place.

Suggestions can now be approved or dismissed in bulk – select a set and act on all of them at once, instead of one card at a time.

Full changelog: lingo.dev/changelog