Launch HN: Quetzal (YC S24) – Stripe for Internationalization
Internationalizing/localizing is hard. You have to comb through your whole app and look for what needs to be translated and manually update your translations every time new stuff gets added. People sometimes hire their own in-house translators, or they send off their translations to humans to be translated, which takes days, weeks, or worse and costs a ton. Internationalization is, of course, super important for user growth and retention, and often neglected until very late, when competitors will make your product for LATAM, APAC, or Europe.
I worked at Slack for three years on the Slack Connect team, building features like Shared Channels and Shared Workspaces, which had millions of users all over the world. Our translation system was slow and painful, often delaying product launches when things were added last-minute, and resulted in context-less and inconsistent translations. Words like "duplicate" could be either an action or a state, depending on if it's in a button or just displaying a status, and words like "Huddles" were translated ten different ways by translators who just wanted to get through as many translations as possible as quickly as possible, hindering adoption and confusing users.
In a parallel universe, but in the same Downtown Oakland apartment, Brendan worked at a retail startup from the founder of Woot, acquired by Amazon, and they brought someone in to manually translate their product into Spanish, which was expensive and took months. Even worse, the translations had to be manually ported over by engineers every time they updated.
Brendan and I have been coding together since fourth grade, starting by making Cydia tweaks on iOS 4, building apps like one of the first Dogecoin wallets (DogeTicker) in ninth grade, and running small businesses fixing computers and making websites. When we realized we both had miserable translation experiences, we decided to work together to make these approaches a thing of the past!
Our solution to these problems is multiple. Firstly, we utilize a custom Babel plugin to traverse the AST and search for user-facing strings that should be translated, eliminating the need to manually comb through the application and gather strings. During builds, we also utilize the AST to provide context to the LLMs on any new text which is then used to give correct translations for different use cases, (e.g. “Duplicate — is it in a button, where it’s a verb, or is in a regular string, where it’s a noun?)
After scanning for strings and wrapping them in functions to display correct translations to the user based on their browser locale, we gather these strings and build time, and submit new strings to be translated and bring in recently translated strings. During translation, we take both the context and similar strings to guarantee consistency. Translation itself using our LLMs only takes a few seconds, rather than days utilizing humans. Of course, we check them afterwards, but LLMs were themselves built for translation and semantic understanding, so they are incredibly good at delivering context-rich, consistent, and great translations better than humans are.
What's great about this solution is that translations are instant and excellent, and you don't have to spend hundreds of hours finding what needs to be translated and passing them off to an external team, you don't have to wait days for bad quality translations, you don't have to maintain a bot to merge completed translations into the codebase, and you don't have to pass context yourself.
We've got a pilot running on our site right now, so if you've got a Next.js project, feel free to try it out using the script on our homepage: https://getquetzal.com. If you've got a project written in some other framework, like vanilla React or React Native, reach out to us (founders@getquetzal.com), we've got npm packages that support these too. If you'd like to see support for something else entirely, like Swift, please let us know and we'll move it up on our docket.
Let me know what you all think about how software translation is today. Is it hard? What approaches have worked or not? We also want to explore problems like how people reach new markets and find customers, so that’s something we’re thinking a lot about as well. If you’ve got funny bad translation stories, I’d love to hear those too, the more shocking and hilarious the better.