brain symbolizing artificial intelligence for natural language processing

Imagine Machines Could Understand Text

Automate human tasks involving text with
Natural Language Processing (NLP) & Machine Learning

See Examples

Natural Language Processing (NLP)
and Machine Learning

Text is everywhere. Almost every process in a company involves manual reading and understanding of text. Most can be automated, so employees can focus on the complex cases. 

Customer Service

Extract intents and entities from emails to auto-suggest answers and improve reaction time.


Automatically detect and preselect fraudulent insurance claims with similar pattern on a massive scale. 


Develop intelligent Chatbots which can answer much more than just weather questions.

Legal Documents

Import your document and find content-related similar documents from any source.  

We create tailored solutions for your
Machine Learning and NLP challenges.

extracting information and intents from email with natural language processing

We help you automate your processes involving text

Natural Language Processing...

NLP is a research field dealing with the communication between human and computers. While human easily communicate through unstructured text, computers need a structured format. To automate your processes you need to transform unstructured text into structured information.

Using different methods from this field you are able to do this. Based on explicit rules and algorithms you can automatically extract information, compare texts and much more.

...combined with Machine Learning

Recent breakthroughs in Machine Learning allow computers to understand text by self-learning algorithms. Without giving explicit rules you can now turn unstructured text into useable data.

We help you automate your processes with texts. is a research & development company that solves problems in the area of Natural Language Processing (NLP) & Machine Learning.

Automate your processes that involve
reading and understanding of text.

Where NLP can solve your problems

We develop individual NLP models for your text processing challenges.
Typical use cases are e.g. processing of unstructured information, anonymization and pseudonymization, chatbots and semantic search.

Take a look at one of our products:
Ask your database for data - without coding.

Chatbot For Databases

With our natural language understanding technology we developed a chatbot for databases. This enables non-technical users to get data from anywhere:  databases, APIs, ERP-Systems and many more.

Natural language interface for databases

AskBy Data is a human friendly natural language interface for databases.

The core technology, AskBy NL Query, is able to translate natural language into any kind of structured format.

For example the user's intent, but also API requests or SQL. That means everyone, even non-technical people, can simply ask for data through their preferred interface and it will be instantly delivered back to the user.

Learn more about our technology in the background.


Our NLP AI Tech Stack

At, we are using the latest insights from Natural Language Processing (NLP) to create and define our models. Especially the field of Natural Language Understanding (NLU) is rapidly developing in recent years due to breakthroughs in the design of task specific neural networks - in particular, these are currently recurrent neural networks in sequence-to-sequence scenarios, as well as attention models. Every year brings new developments that outperform old benchmarks, for example the ones in the GLUE benchmark - a new de-facto standard in the NLP community. This is why it is so important to be up-to-date in this field.

For training language models, we use an internally developed architecture inspired by BERT, an unsupervised transfer learning approach based on the Transformer that outperformed current state-of-the-art models on various tasks in late 2018. From our experience, those models require only little fine tuning to work very well on tasks like document representation, document classification and semantic search. In general, we argue that these models are the right choice for any language task that requires a deeper understanding of the content of texts.

Another scenario and one of the core technologies of AskBy is natural language to formal language translation. For that purpose, we developed a new kind of recurrent neural network architecture called Nefisto (Neural finite state output). Translating to formal language has its own challenges - due to the strict syntactical requirements on the output. For this reason, Nefistos allow to restrict their output using simple grammatical rules. This allows to do translation not only to complex sequences, but even to complex hierarchical calculation trees. Have a look on our calendar demo to see a simple example what it can do.

Often times, especially (but not only) when translating to formal languages, it is difficult to acquire the right amount of data for the task. Classically, training data is generated by humans. But if the prediction space is combinatorially big, it is intractable for a human to write down samples line by line, since the prediction space might grow faster than exponential. For this purpose, we developed a small programming language called Larala (Language randomization language). It gives its programmer a more expressive tool to create training data and capture larger parts of the prediction space with (asymptotically) much fewer lines of code. It was originally developed for AskBy NL Query, a product translating natural language to database requests. In this scenario, there was initially no training data at all - but using Larala we were able to build a system that works extremely well.

So if you think you don’t have enough training data or no training data at all - we might still be able to help you. Get in contact with us.


Would you like to learn more about AI?

Take a look at our workshopsAI and NLP

or let's meet for coffee first