AI in Localization

OpenAI hype has made many teams believe that a simple API call to GPT-4o is all they need to translate their product. This might work for a simple one-pager or situations where you don’t necessarily need the translation to feel native to your audience. However, there is a big difference between translating a sentence in a chat box and localizing a product at scale. OpenAI is a powerful engine, but it is not a localization platform. It lacks the infrastructure to manage a product. To truly understand why, we need to look at the gap between a raw AI model and a professional localization ecosystem. Besides the comparison, we want to show you how to get the maximum of both worlds: OpenAI and Crowdin.

We found that there’s not much clear information on AI translation costs. So we decided to make an experiment to find out: How much does it actually cost to translate a real project using AI localization in Crowdin? Important: Often, this price will differ from platform to platform. It's worth noting that our price will be clearly lower. Why? While many platforms add surcharges, Crowdin charges no fees for your AI consumption. You pay exactly the direct API rates charged by providers like OpenAI, Google, and Anthropic. This makes Crowdin the most cost-effective TMS with the widest choice of LLMs. This gives you the freedom to experiment with different AI models and find the best fit for your needs while keeping your expenses at a minimum.

If you have ever tried to use AI for professional translation, you know the drill: you give it a massive list of instructions, and it starts out great... then it gets tired. It forgets your glossary, ignores your style guide, or starts hallucinating. In our latest Crowdin Power Up episode, Dorota Pawlak and Stefan Huyghe looked at why this happens and how a new Crowdin app called AI Pipeline actually solves it by changing the way we talk to AI models.

Nowadays, AI localization is an art that requires more than just linguistic knowledge. As AI becomes an integral part of the localization workflow, mastering the art of crafting effective prompts is important for translators and localization professionals. This article was created in collaboration with professional linguist, localization consultant, and AI trainer Dorota Pawlak. Find out advanced prompting strategies and examples for using Agentic AI in Crowdin to enhance various aspects of the localization process.

For decades, making your business multilingual meant a slow and expensive process of translating word-for-word. Now, with AI localization, every business can afford to go global. But simply changing the language is not enough; you need to capture the culture, the tone, and the market nuance for every single audience. AI localization is not just a faster version of old-school machine translation. Based on Large Language Models, it produces translations that are tailored to specific local cultures rather than language-to-language interpretation. Read on to discover how AI, combined with human expertise, is making it possible to launch international products faster. Learn what the Crowdin platform is, and which localization tools can help you create AI-powered workflows to optimize your budget. Editor's Note: AI Technology moves fast. Tools that work today may be useless tomorrow. To make sure the content is always up-to-date, we review and update this article every few months with the most relevant insights and newest tools.

In localization, context is king. But what if your most valuable brand context – the nuances, the terminology, the single creative phrases – was locked away? For too long, your AI models couldn't fully use that data. Previously, we've relied on traditional Translation Memory (TM) fuzzy matches, often overlooking anything below 50% or even 10% similarity. Those “tiny matches” contain critical stylistic and terminological clues, but they rarely get displayed or used in our workflows. Crowdin's new Vector Cloud app is here to change that, transforming AI translations, by enabling ai to use the most of available context. In the fourth episode of Crowdin Power Up, host Stefan Huyghe and AI localization expert Dorota Pawlak dived into Vector Cloud. They demonstrated exactly what this is, how to set it up, and how to work with it to transform your AI translation workflows. <ResourcesCTA title="Build an AI Localization Workflow with Crowdin" description={null} class="from-gray-900 to-gray-700 dark:from-gray-800 dark:to-[#0B1918]" titleClass="text-4xl! font-semibold" badge="Free Guide" ctaText="Download Now" ctaHref="https://crowdin.com/learn/ai-localization-workflow-ebook?utmterm=ctacrowdinblog" ctaId="ai-localization-workflow-cta" imgSrc="ai-localization-workflow-books.png" showPodcastLinks={false} />

Localization often takes a lot of effort, so saving time on manual tasks lets you focus on quality. In a recent Crowdin Power Up episode, host Stefan Huyghe and AI localization expert Dorota Pawlak introduced new features that make your Crowdin workflow smarter and more efficient. Keep reading to discover how these platform updates will: - Eliminate ambiguity by automatically flagging unclear strings. - Handle bulk actions like a pro with simple text commands. - Automate workflows for tasks you perform every day. You'll see how these new tools help translators who are ready to embrace the future of AI-powered localization. Check the full episode on YouTube.

Model Context Protocol (MCP) is a technology that allows you to connect large language models (LLMs) to external, dynamic data sources and tools to provide more contextual information. Unlike Retrieve Augmented Generation (RAG), which accesses static documents, MCP connects to live resources that change constantly, such as code repositories or content management systems. This dynamic access helps LLMs provide more accurate and context-rich outputs. MCP usage can reduce "hallucinations" in which the AI generates incorrect information.

What if there was a way to make AI in localization not just faster and more cost-effective, but also smarter? Enter the Agentic AI era, which transforms how we approach translation and localization. In this article, we'll explore: - What Agentic AI is. - How it differs from earlier AI versions. - How Agentic AI works. - Its impact on the localization industry. - Crowdin's approach to Agentic AI (features, examples, and how it helps translators).

Lightning fast, continuous localization. Decent quality. Super affordable. All automated with no humans in the loop. This guide shows you how to build a multilingual product on autopilot using Crowdin. The workflow is tech stack agnostic and suitable for web, mobile and desktop applications, as well as their documentation and marketing materials. Let AI to have all the information it needs to produce the best possible AI translations. You still are able to bring in human linguists to improve translations. Prerequisites: You have an internationalized web or mobile application. This means that all translatable texts from the UI have been extracted into the resource files. The implementation time of this guide is 30 minutes. <BlogCTA title="Looking for a Complete General Guide?" buttonUrl="https://crowdin.com/blog/ai-localization" buttonText="Read More About AI Localization" buttonId="read-more" />

Accurate translation is essential to facilitate global collaboration. Traditional translation methods often require significant time and resources. Combining Crowdin AI and human translations offers faster and more consistent results. By harnessing the power of AI, you can enhance its translation capabilities and optimize resource allocation. Discover how AI revolutionizes the localization process and workflow by enhancing translation accuracy through contextual understanding in this article.

If you're curious about how Crowdin AI can enhance your localization projects, this article answers some frequently asked questions about price, customization, and best practices. Let’s discover if an AI can translate and the best way to use AI tools for language translation. <YouTubeEmbed id="ZqfvNIMpp4Q" />