What are the challenges in building an NLP engine?

Building an NLP engine requires a deep technical knowledge to make it work

Natural Language is not a piece of cake. Processing the way people talk is a much more complex science than it seems and requires highly specialized resources. This leads to an expensive and laborious procedure in order to get AI ready to be used.

How can we work it out?

Get the NLP elements you need to make your AI understands users

Bitext Natural Language ready-to-use tools are there to help developers and integrators face problems related to language diversity, long training times and lack of vocabulary. So, now you can be NLP technology-agnostic.

Which one meets your needs?

Improve your model with better word embeddings

Increase the accuracy in your Machine Learning models with better semantic representations

Word embeddings are the base of most Machine Learning models that deal with text: bots, classification, sentiment, etc. But traditional embeddings have fundamental flaws in how they deal with basic content, assigning similar representations to opposite concepts (such as love vs. hate). Our embeddings incorporate additional linguistic information to overcome these obstacles and provide a significant accuracy boost.

  • Advantages:
  • Higher accuracy

  • Multilingual

  • Broad coverage
    (formal & informal)

Run your NLP engine on your device

Unleash the power of your IoT edge devices

Gone are the days of depending on unreliable data connections to offload processing to cloud-based NLP pipelines. Our NLP platform provides on-device parsing in over 20 languages. Written in portable C, it offers fast processing and low footprint on virtual any device.

  • Advantages:
  • Performance

  • Privacy

  • Reliability

Make your NLP engine understand up to 50 languages

Get your lexicon ready to be uploaded to your NLP engine and reach users worldwide

If you want your AI to understand users in any language you must teach it not only the meaning of the words, but also their connotations together with the way they are processed. With Bitext, you can obtain very rich lexicons to feed your bot.

  • Advantages:
  • Complete set of
    data features

  • 50 languages available
    including Spanish & Hindi

  • Trusted by
    market leaders

  • Easy integration
    with any bot platform

Reduce training time of your Machine Learning

Get your data carefully tagged to boost your Machine Learning training overnight

One of the toughest tasks of Machine Learning training is tagging the data required for your engine to be smarter. Bitext automatically classify your raw data in more than 20 languages by tagging features such as lemma, POS or sentiment, so that you do not only save time, but you also get more accurate results.

  • Advantages:
  • Complete set of
    data tagging

  • 20 languages available
    including Spanish & Hindi

  • Easy integration
    with any bot platform

  • Helps you comply with

Improve your bot’s understanding skills

Get the most accurate NLP functionalities to improve your Machine Learning bot understanding

Your Machine Learning bot needs good NLP skills to understand users. Bitext can incorporate these core NLP functionalities to your Machine Learning engine or improve even yours at ease, so that you don’t need to care about complex NLP issues.

  • Advantages:
  • Increase accuracy,
    (even with negation)

  • 8 languages available
    including Spanish

  • No previous data

  • Easy integration
    with any bot platform

Ready to go and easy to implement NLP engine

Discover why your NLP isn’t working properly and make it fully conversational

NLP systems are not that easy to manage. That’s to say, if you don’t feel like racking your brain, we can get that work done for you. Let us analyze your current NLP to detect possible flaws and visible improvements, or even help you develop a NLP system from scratch.

  • Advantages:
  • Reach over 90%

  • Comprehensive data

  • Carrying out
    production tasks

  • Needs identification

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