Cloud Translation API

Document Translation With Layout Preserved

Translate PDFs, DOCX files, and PPTX decks while keeping the original layout, fonts, and embedded images intact. The translateDocument endpoint accepts a base64 input or a Cloud Storage URI and returns the translated file, which removes the need to manually rebuild the document after translation. Useful for legal, regulatory, and sales-enablement teams that need translated artefacts that still look like the original.

Batch Translation Pipelines

Translate large corpora of text or many documents in a single asynchronous job using batchTranslateText or batchTranslateDocument. The job reads input files from Cloud Storage, fans out across Google's translation backend, and writes output to a destination bucket, which is the standard pattern for catalogue localisation, knowledge-base translation, and corpus migrations. A single job can cover hundreds of thousands of segments without rate-limit babysitting.

Adaptive Translation With Custom Datasets

Use adaptiveMtTranslate with a customer-supplied parallel dataset to produce translations that match an organisation's tone, terminology, and product names. This is useful when generic NMT output mistranslates brand terms or industry jargon. The endpoint takes a dataset reference plus the input segments and returns translations adapted to the supplied examples without requiring full custom model training.

Agent-Driven Multilingual Workflows via Jentic

AI agents discover the Cloud Translation API through a single intent search on Jentic, load the input schema for the operation they need, and execute the call without writing OAuth boilerplate or copying spec snippets from Google's docs. Jentic isolates the OAuth token in its vault so the agent never handles raw Google Cloud credentials, which is essential for multi-tenant agent deployments. Integration time drops from a multi-day OAuth setup to a single search-load-execute call.