Translation is one of those things that sounds simple until you're staring at 10,000 SKUs that need to go live in six languages by next month.
Most teams have tried a few things. Agencies that are expensive and slow. Running products through DeepL one at a time. A patchwork of tools that sort of work but don't talk to each other.
The good news: AI translation tools have gotten significantly better. The tricky part is figuring out which one actually fits how your team works, because a tool built for translating legal documents isn't the same as one built for product catalogs.
Here's how the options stack up.
The real translation challenges for enterprise ecommerce
If you manage a large product catalog across multiple markets, these will sound familiar.
Speed to market
Every new product needs to be translated before it goes live in other regions. For teams with thousands of SKUs, this creates a constant backlog. Seasonal refreshes, new launches, and product updates all compete for translation bandwidth, creating bottlenecks for international teams.
Cost at scale
Translation costs scale with your catalog. Thousands of SKUs multiplied by multiple languages, plus re-translation whenever product data changes. Whether you're using agencies, freelancers, or in-house teams, the costs add up really fast.
Brand consistency across regions
When translation is handled by different vendors or regional teams, things start to drift. Terminology varies, tone shifts, and your product content ends up feeling inconsistent across markets, even if each individual translation is technically accurate.
Fragmented workflows
For many teams, translation is disconnected from where product content actually lives. Content gets exported from a PIM, sent to a translation tool or agency, then imported back. Every handoff introduces delays and room for error.
What to look for in AI translation for product content
Not every translation tool is built for product catalogs. Here's what actually matters when you're translating structured ecommerce content at scale.
Built for catalog structure
Product content isn't just paragraphs of text. It's titles, bullet points, descriptions, attributes, specs, and variants, each with different constraints and purposes. The right tool understands this structure and handles each field appropriately rather than treating everything as one big block of text.
Brand voice control
Accurate translation isn't enough. Your product content needs to sound like your brand in every language, which means you need tools that let you define tone, terminology, and style, and apply those rules consistently across all translations.
Localization, not just translation
Literal translation often misses the mark. Effective localization adapts phrasing, idioms, and even SEO keywords for each market. The goal is content that feels native to local shoppers, not content that obviously reads like it was translated.
Integration with your stack
Translation that lives outside your content workflow creates friction. The more tightly it integrates with your PIM, ecommerce platform, or content system, the less manual work required to keep everything in sync.
Scale without linear cost growth
If your translation costs scale directly with SKU count and language count, the math becomes unsustainable quickly. Look for pricing models that actually make sense at your catalog size.
Quality control built in
Even the best AI translations need review for certain content types. Look for tools that include approval workflows, editing interfaces, and the ability to flag content for human review when needed.
Top AI tools for ecommerce translation
There's no single "best" tool. It depends on what you're translating and how your team works.
DeepL
Best for: High-quality document translation, including marketing copy, product descriptions one at a time, and content where nuance matters.
DeepL has a reputation for natural-sounding translations, especially for European languages. It handles tone and nuance well, making it a strong choice for polished marketing content or individual product descriptions. Teams typically paste or upload content, get a translation, and bring it back into their systems.
ChatGPT Translate
Best for: Quick, conversational translations where you want flexibility to adjust tone on the fly.
OpenAI launched ChatGPT Translate in January 2026 as a dedicated translation interface. It supports 50+ languages and lets you request adjustments like formal vs. casual tone, regional phrasing, or simplified language. Useful for ad-hoc translations or when you need to quickly check how something sounds in another language.
Weglot
Best for: Brands that want their storefront multilingual quickly without touching backend systems.
Weglot sits on top of your website and automatically translates everything displayed to visitors. Setup takes minutes: Install a plugin on Shopify, WooCommerce, or your CMS, and your storefront is available in multiple languages. It handles multilingual SEO and auto-detects new content. It's focused on translating your website presentation layer, so it works well for brands whose primary need is a localized storefront.
Smartcat
Best for: Teams managing translation workflows with a mix of AI and human review.
Smartcat combines AI translation with a marketplace of 500,000+ human translators. You can choose AI-only, human-only, or hybrid workflows where AI translates and humans review, and the platform learns from edits over time to improve quality for your specific content. It integrates with PIMs like Salsify and offers solid project management features. It's a good fit for teams that want flexibility in how they manage translation quality and workflows.
Hypotenuse AI
Best for: Ecommerce teams translating product catalog data at the source.
Hypotenuse AI is a product content platform with translation built in, rather than a separate translation tool that integrates with your systems. Content lives in one place, and translation happens where the content already exists. Brand voice is configured once and applies to both content generation and translation.
The platform understands catalog structure and handles titles, descriptions, attributes, and variants appropriately. For teams that want translation without adding another tool, workflow, or vendor to manage, this approach eliminates the fragmentation problem entirely.
There's onboarding involved to get brand voice and integrations set up, so it's not instant like a copy-paste tool. But once configured, translation runs from the same place your content lives.
Phrase
Best for: Enterprise localization teams managing translation across many content types.
Phrase is a full translation management system built for localization professionals. It supports 30+ machine translation engines, translation memory, terminology management, and workflow automation. You can train custom AI models on your past translations to match brand voice. It's a strong choice for teams with dedicated localization resources managing translation across websites, support docs, marketing content, and product catalogs.
How to evaluate AI translation tools for your catalog
Before choosing a tool, map out your requirements.
Map your current workflow. Where are the bottlenecks and handoffs? Where does translation actually slow things down?
List your target languages. Which markets do you serve today, and which are you expanding into? Do you need regional variants like LATAM Spanish vs. Spain Spanish, or simplified vs. traditional Chinese?
Check language coverage. Not all tools support all languages at the same quality level. Verify that your priority languages are well-supported, not just listed as available.
Define brand voice and terminology requirements. Do you have existing style guides or glossaries? How important is consistency across markets?
Identify integration needs. Where does your product content live, and what systems would translation need to connect with?
Test with a representative batch. Run a sample of real products through any tool you're evaluating, including different product types, different content lengths, and your most important languages.
Assess total cost at your scale. Model pricing at your actual SKU count and language count, some tools charge per word, others by number of languages, or both.
Conclusion
The right translation tool depends on what you're translating and how your team works. DeepL is great for polished, one-off translations. ChatGPT Translate is handy for quick checks. Weglot gets your storefront multilingual in minutes. Smartcat and Phrase offer robust workflows for teams with dedicated localization resources. Hypotenuse AI is great for an end-to-end workflow.
For enterprise ecommerce teams managing large product catalogs, the key question is whether translation should be a separate workflow or built into where your product content already lives.
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