Categories: FAANG

A closer look at Translation Hub: Enterprise translation made easy

Hello! ¡Hola! 你好! नमस्ते! Bonjour! Being greeted in your own language can instantly put a smile on your face, and organizations around the world recognize that messages become more inclusive and powerful when translated into many languages. 

As the Head of Product Management for Translation AI at Google Cloud, I am always looking to make our user’s lives easier when it comes to language tools—like Google Cloud’s Document Translation API, which has been used to translate over 2.5 billion documents across Google Translate and our Cloud customers. 

But during my time working on translation products, I have seen enterprise enterprise users making compromises, like sacrificing cost and speed of translation for quality, or paying much more for high-quality translations and making peace with the slow turnaround times and high costs. That’s why we are excited to see momentum building behind Translation Hub, which launched earlier this year. Built to address organizations’ localization and translation challenges and delight users with an incredibly intuitive and administratively simple offering, Translation Hub makes it easy to translate content at scale—users just need to select the files to be translated, choose the output languages, and then they’re off and running.

In this article, we’ll take a closer look at Translation Hub’s powerful features, and the ways it is helping customers do more with their content. 

Enterprise translation, reimagined: fast, lean, and intuitive

Translation Hub is a fully-managed, self-serve translation offering, powered by Google AI and built for the enterprise. With Translation Hub, businesses can instantaneously translate content into 135 languages with a single click, via an intuitive interface that integrates human reviews (i.e., a “human in the loop”) where required.

Translation Hub is designed to be both easy to manage and use. Each organization’s Translation Hub administrator uses the Google Cloud console to onboard and manage business users, typically by adding their email, which triggers an invite to the business user. Once a business user is added, they can sign in and start requesting translations and post-editing reviews. 

With advanced features like “Glossary” and “Custom Translation Models (AutoML Translation),” Translation Hub makes it easy for enterprises to control the terminology and inject domain-specific context to meet their unique needs. Furthermore, Translation Hub ensures that organizations own their Translation Memory, for use in future translations or to leverage as a rich, human-validated source of training data for custom translation models (e.g., AutoML Translation). For example, when a user edits a phrase or segment through Translation Hub, this is immediately captured and used in the next translation for all future users who initiate translation where the same content or segment appears. 

One of my favorite features is that Translation Hub preserves the layout and format of documents, saving both time and money. And while Translation Hub works with Google Drive (you can ingest and export documents to Drive) and is compatible with all our Google Workspace content sources (e.g., Slides, Docs etc.), it also supports many of the most commonly used formats, like documents and presentations created in Microsoft Office, and scanned and native PDFs.

Organizations need to be able to share the output of AI-powered translation with localization teams or agencies, for review. They need to save time by leveraging glossaries or customer machine learning (ML) models. They need these capabilities in one cohesive platform—and they need all of this to be user-friendly for all kinds of business users. It’s the difference between being able to automate translations in a few scenarios and being able to translate at scale. Google Cloud’s mission is to accelerate every organization’s ability to digitally transform, and with Translation Hub, our customers can leverage the best of AI for their content translations without sacrificing speed, quality or cost. 

All of Google’s Translation Innovations within a single product

Translation Hub uses Google Cloud’s Translation API, AutoML Translation, and innovations in Neural Machine Translation Quality Prediction and Translation Memory—all technologies we’ve put to good use inside Google. For example, our localization teams have realized more than $80 million in cost avoidance and savings since 2021, using Google Cloud AutoML Translation and localization expertise. 

“In just three months of using Translation Hub and AutoML translation models, we saw our translated page count go up by 700% and translation cost reduced by 90%,” said Murali Nathan, digital innovation and employee experience lead, at materials science company Avery Dennison. “Beyond numbers, Google’s enterprise translation technology is driving a feeling of inclusion among our employees. Every Avery Dennison employee has access to on-demand, general purpose, and company-specific translations. English language fluency is no longer a barrier, and our employees are beginning to broadly express themselves right in their native language.” 

To get started with Translation Hub, visit our solution page, and for a deep dive, check out this Google Next ‘22 session, including more details about Avery Dennison’s use case.

Related Article

New AI agents can drive business results faster: Translation Hub, Document AI, and Contact Center AI

Google Cloud announces new AI agents — Translation Hub, Document AI Workbench and Document AI Warehouse — and continues to update Contact…

Read Article

AI Generated Robotic Content

Recent Posts

Does anyone else can’t stand ComfyUI and prefers classic Automatic/Forge UI or it’s just me?

EDIT: I can't believe how many great and useful replies I've got, and not a…

2 hours ago

Serving Multiple Users at Once: How Continuous Batching Keeps LLM Inference Efficient

This article is divided into four parts; they are: • The Problem with Static Batching…

2 hours ago

Everyone Has Their Targets Set on the MacBook Neo

Dell, Microsoft, and others are unveiling new laptops to compete directly with the Neo, but…

3 hours ago

Photon-driven synapse advances low-power neuromorphic systems

Modern artificial intelligence systems rely on moving large amounts of data between memory and processors,…

3 hours ago

Anima – Sharing Some Prompts and Results

Been experimenting with Anima lately and ended up spending way too much time refining prompts.…

1 day ago

Keychron K2 HE Concrete Edition Review: Rock-Solid Typing

Keychron's K2 HE Concrete Edition sounds like a cute gimmick, but as I discovered, there's…

1 day ago