Translators couldn't determine when AI suggestions could be trusted.
Expose historical matches and confidence directly inside the editing workflow.
Translators stopped second guessing the AI: unnecessary edits dropped 62% as confidence became visible instead of assumed.
Reviewers and project managers had no visibility into why translation decisions had been made, forcing teams to rely on emails and manual follow-ups.
I introduced a persistent audit trail that captured every edit, reviewer action, and decision directly at the segment level, giving every role shared visibility without leaving the document.
The email archaeology ended. Every decision is traceable at the segment level, and disputes resolve by looking, not asking.
Conversations about translations happened in email threads, making context difficult to trace and slowing collaboration.
Instead of separating communication from the work itself, I embedded threaded discussions directly within each translation segment so decisions remained attached to the content they referenced.
Questions live next to the segment they are about, cutting PM interruptions by 40% and keeping context attached to the work.
Terminology guidance existed, but translators had to leave their workflow to search for it, increasing cognitive load and inconsistencies.
I surfaced client glossaries directly inside the editor, providing contextual terminology recommendations exactly when translators needed them.
Terminology stopped being a lookup task. Consistency improved while translators stayed in flow.
Formatting tags had to be managed manually, making translation slower and increasing formatting errors.
I designed an interaction model that allowed translators to copy, edit, and reposition formatting tags independently of the translated text, preserving document structure without interrupting the writing flow.
Formatting errors stopped surviving to delivery, and tag handling went from a chore to a single interaction.
Quality assurance relied heavily on manual reviews, making repetitive errors difficult to detect before delivery.
I integrated automated QA checks directly into the translation workflow, allowing linguists to identify terminology, spelling, and formatting issues before submitting their work.
Repetitive errors are caught while translating, not after delivery, making quality continuous instead of a final checkpoint.
Identical source segments were translated repeatedly, creating unnecessary work and inconsistencies.
I introduced automatic propagation of identical translations while allowing linguists to override suggestions when context required different wording.
Identical segments are translated once. Repeated work disappeared while linguists kept the final say.