Language independent NLP makes it a lot easier for you to build bots in more than one language. If you build a bot in for example English and you properly train it’s NLP in that language, it will already understand more than 100 other languages out of the box.
Yes, you read that correctly. Our NLP is actually language independent. Here is an example for our Choo Choo bot. If you have ever followed our tutorial, you know this bot that lets you order train tickets. Since the tutorial is in English, you might think your bot only understands English. But that is no longer the case. Go into the NLP – Test tab and type the following sentence in English: “I want to book a train ticket”.
As you can see in the screenshot above the model is 99% confident that you want to book a train ticket. Now repeat the same for all the other languages you might think of you can use Google Translate or even better DeepL to give you the correct translations for languages you don’t speak.
- French – “Je veux réserver un billet de train” – 99% confident
If you have ever built a bot before, you know that training and maintaining the NLP is the part that requires the most effort. And once you make your bot multilingual, this effort is doubled every time you double the amount of languages your bot supports. We say: no more! Thanks to our language independent NLP you need to do this work only once, for one language. For the other languages it just works out of the box. You only need minimal effort to adapt your NLP to very language specific expressions.
If you build a bot in one language you spend 80% of your time building the conversational flows and 20% of your time on training the NLP. Previously you had to redo the effort of training the NLP for each language. Thanks to our language independent NLP this is no longer the case. If you build a bot that supports 5 languages, you no longer spend 5 times the NLP effort. You will save 75 to 80% on the NLP effort or around 40% of the time spent building a bot.
Once a bot goes life into production about 95% of the maintenance effort is spent on the NLP. Traditionally if you build a bot in five languages you end up with close to five times the maintenance effort. But with our language independent NLP this is no longer the case and you will save up to 75% of the effort maintaining your bot.