True multilingual AI capabilities

Even within the same country, languages ​​can differ greatly and markets are therefore usually multilingual. With this in mind, we have trained a model that understands over a hundred languages. Not only that - if you teach it a task in one language, it can also do it in the rest of the languages ​​it knows.

We crush language barriers for you.
Build your own AI model in an afternoon.
Coding knowledge not required.

What benefits can you get with Labelf?

Global Expansion

Do you have data coming in from around the world? Do you plan to have data from around the world in the future? No problem, Labelf gives you the opportunity for global expansion.

Teach it once

Labelf already knows over 100 languages and retains that skill when you teach it to perform tasks in one language meaning that you only have to teach it once in the language that you know.

Language level insights

What does people think that writes in Swedish? Do we have a problem that is unique for Germans? Labelf knows which language your data is in.

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Easy to use, easier to start

Step 1

Connect with your platform

Seamlessly integrate Labelf with your customer support systems.
Step 2

Create and train your model

Labelf AI model can learn from your existing labeled tickets, or you can start training while customizing the model to your needs.
Step 3

Activate your model

Start using the AI model and enjoy the intelligence and convenience!

"The implemented solution ended up saving several minutes per nonconformity allowing the auditors to focus more on interacting with the customer during each audit."

Karin Claesson
Systems Specialist, Qvalify

Can’t wait to build your own AI model?

Deploy automated ticket routing and improve your customer support today.
Sign up for a free trial or contact us to learn more.

Contact us

Get in touch and let us know how we can help.

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What are multilingual models?

By training the model in several languages ​​with our unique technology, the model learns what texts mean in different languages ​​at the same time. In normal cases, this means that you can then train a multilingual model in one language and then it can do the task in that language.

What we do with our true multilingual model is we train it in such a way that it maintains its language skills and doesn't forget about the other languages. This means that you can train it in one language and then it works in over 100 languages!
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