• Natural Language Processing

    These Deep Learning algorithms add more meaning to the text masses by detecting e.g. nouns, adjectives, objects and more syntactics.

  • Classification algorithms

    Perfect fit for automatically tagging your text amounts when you already know the functional classification scheme.

  • Clustering

    Clustering algorithms automatically detect topics for you.

  • Interactive visualization

    During the years we have developed ways of making machine learning results easily understandable for our customers. Most of them are interactive.

  • Semantic Monitoring Systems

    Our semantic contextualization algorithms help you keep up to date with how the context of your business is changing.

  • Topic Modeling

    Being part of unsupervised ML, these algorithms automatically find structures within huge text amounts.

  • Deep Contextualized Embeddings

    If you want to find sentences with similar meaning but written in different words – these algorithms will help you.

  • Word Embeddings

    Detecting context of a word within huge amounts of text becomes easy with semantic algorithms. Results are often visualized with Semantic Maps.

  • Data-driven Personas

    Market segmentation and customer profiling done the digital way: Turn user generated-content into stereotypes within days. No interviews needed.

  • Semantic Maps

    The right interactive visualization to zoom in and out of semantic similar words and explore these maps on various hierarchical levels.

  • Hyperlocal Influencer Maps

    Finding influencers that fit your product and brand message the data-driven way.

  • Interactive Dashboards

    The right tool to explore huge text amounts both on a broad and deep level. The NIZE Online Radar relies on this dashboard.

Find out what machine learning technologies can solve your text challenge.