Natural Language Understanding

Natural Language Understanding

Faktion has the most accurate and complete Natural Language Processing solution on the European market. Through our NLP framework, we can provide exceptionally fast results building on our earlier work and research. From classification, document or email processing, information extraction to personality, demographical and mood analysis.

We build state-of-the-art, custom NLP solutions for West-European languages

The most accurate in the market for West-European languages

We have benchmarked the performance of our engines extensively against other frameworks. Faktion continues to invest into researching and improving the Faktion NLP framework. Our NLP research team currently consist out of 8 full time Machine Learning engineers that love pushing the boundaries of what is possible with natural language and speech recognition.

Fast time to value

By building on our existing experience and code, we can deliver projects faster, with better performance and at lower cost compared to providers who have to begin from scratch. Our framework consist of reusable components that are combined in the form of pipelines. Different use cases provide different pipelines, and we take care of giving you the best state-of-the-art results without worries.

Customizable when needed

Some problems are so specific that even the best standard components are not sufficient. In that case, we can create custom components for you. Read more in this blog post about the need for custom models.

How can you use NLP?

Our framework is used by some of the world’s largest enterprises. Example applications include:

  • Information extraction. It is a sad given that most of the information in the world is in an unstructured form. Recent advances in information extraction however have made it feasible to automate large parts of the information extraction process. By using machine learning, ontologies and parsing trees, Machine Learning models can find connections and patterns between words with a high degree of accuracy. It saves companies immense amounts of time to have the information they need in a structured format.
  • Intent recognition and entity extraction. We have benchmarked our intent recognition models and have found that they are 2 to 10% more accurate than the NLP models of major technology providers. Our models can also run on premise, in a private cloud and be adapted to suit specific use cases.
  • Classifying and tagging text. Whether the data source is tweets, e-mails, documents, website or books, you want to be able to better search, quantify and gain insight in your existing and future collections. At Faktion, we continuously improve our text classification models to provide the highest accuracy.
  • Regression and prediction. Unstructured text can be used as an additional input for regular predictive models. Predictions from unstructured text are used in insurance claim processing, AI jury members, predictive maintenance on inspection logs, etc.
  • Automatic response generation. Knowing what people are saying is great, but being able to respond semi-automatically or fully automatically is where you can save time and money. Depending on the use case, AI can be used to suggest answers, choose the correct answer from a number of predefined templates, or fully generate text itself.
  • Document similarity and script adherence. We have experience in analysing call center transcripts for script adherence metrics and quantifying the impact of that.
  • Voice, translation, transcribing. We have speech recognition models for Dutch, French and English. These can be customised to your use case and deployed anywhere from your private cloud to your own edge devices.
  • Personality, demographical and stress analysis. All people write and talk in different ways. By analysing their voice timbre, language patterns, emoji use, vocabulary, etc., you can reasonably estimate a person’s age, gender, level of education, or stress level at the moment. This data can be used for personalised advertising, gaining more insight or reacting in a more personal way.