Create value from text

Combining human & machine intelligence, we allow companies to save time and leverage the value of their text data.

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Text data is everywhere: Let it be in simple Word or PDF documents, emails, online reviews, comments, or transcribed phone calls.

While this data contains lots of valuable information, the unstructured nature of text makes it difficult to analyze and use its information. With natural language processing, we can make it accessible and unlock its value.

We help companies use NLP to save time, scale the amount of data they process, and increase the quality of their products and services. 

Creatext helps you analyze your text data

Use cases

We build customized NLP solutions. Our projects range from text analytics to automatic text writing, always building a bridge between state-of-the-art NLP research and business applications.

Social Media Comment Analytics


Too many social media comments to go through? We've got you covered!

Bot & Hate Speech Detection


Detect and automatically delete inappropriate comments on your platform.

Information Synthesis


Summarize key information from thousands of documents in one well-organized table.

State-of-the-art NLP for your business!

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Solutions

Our toolbox contains state-of-the-art natural language processing technology to your business problems.

Document classification

Assign your documents to different groups or add tags to your texts.

Summarization

Get concise valuable information from long text documents.

Paraphrasing

Adapt text content to your various needs, translate it from one style to another.

Text generation

Write beautiful text automatically, in your user’s language style.

Question answering

Let our algorithms look for the information you’re searching for in your text documents.

Information extraction

Extract addresses, names, and other information from texts and store them in a structured way.

Let's start your NLP journey together!

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Meet our team

Having met during our Statistics studies at ENSAE Paris, we share both a strong interest in deep learning for real-world applications and an in-depth technical understanding of today’s state-of-the-art language models. 

Lukas Kemkes

Bridging business and technical experience, acquired at Tesla, Lukas is our clients' first point of contact. Building on his  background in NLP from Paris-based startup CybelAngel, he recently developed a model to summarize news articles automatically.

Manuel Tonneau

After applying machine learning at major institutions (The World Bank, Société Générale), Manuel is now using language models to improve the way machines understand and write text. In his master thesis, he improved the state-of-the-art in sentiment analysis for financial texts.

Jérôme Bau

Having taught chatbots how to talk at Botfuel in Paris, Jérôme took a deep-dive into AI research at the Tokyo-based research lab Riken AIP. Passionate about natural language generation, he later helped diverse clients automate their text content generation as NLP freelancer.

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