Incredible how fast time does go by in the end. The first ten years just flew by 🙂 Great people, interesting projects and steep learning curves across all dimensions, all with the goal to develop innovative AI solutions for complex real-world problems.
A sincere thank you to our fantastic colleagues. It’s them who make LangTec who and what we are today. Thanks also to our wonderful clients and project partners. Without their trust in our performance and expertise our growth simply would not have been possible.
We are looking forward to the next 10 years and are curious to see how LangTec’s focus topics text and data analytics, machine learning and artificial intelligence will develop. One thing is for sure: it’s going to be an exciting ride 🙂

We are delighted that our concept for the AI solution AlatUno was selected for federate funding in the CIVIC innovation contest. AlatUno is a cooperation that will be realized with our wonderful project partners Entwicklungswerk gGmbH and the Digi Sapiens – Digital Learning GmbH. The goal of AlatUno is strengthening participation by AI-based simplification of complex application processes in the public sector.

The online award ceremony with Federal Minister of Labour and Social Affairs, Hubertus Heil, took place on March 10, 2021. 25 particularly innovative projects out of the significantly more than 100 submissions were awarded with a sponsorship of EUR 20,000 each.

Our team is growing further in the Data Science and Machine Learning division: From the second half of March onwards, Nilesh will be joining our team as Senior Machine Learning Engineer. Nilesh has extensive experience in software development and semantic image segmentation based on deep learning approaches. Great to have you join us, Nilesh, and welcome aboard!

We are adding another member to our team assistance and are very pleased that Bennet is joining our administrative support. Extending a very warm welcome to you at LangTec, Bennet!

Great to have you on board with us, Soumya. We’re super-happy to have you join our natural language processing (NLP) team. Your extensive prior experience in the analysis and the tuning of large-scale statistical language models you will be able to put to action directly in a number of our on-going client projects. A very warm welcome to you and all the best for your start with us! 🙂

We are very happy to announce that Mahsa will be starting her Master thesis project on artificial intelligence with LangTec on 01 February 2021. In her research Mahsa will investigate deep-learning approaches to processing filled forms and shall refine existing results from previous research done at LangTec.

Large banks like our new client have long, extensive contract documents in many languages … but, regrettably, no time to search them manually for key information. To this end, LangTec develops automated solutions for information extraction that show which information can be found where in the hundred-plus-page contract documents. Exactly this is also what we will be doing for our new client. We are grateful for the trust placed in us and look forward to the new consulting mandate!

And another text classification engagement! We are thrilled to support our client’s top-notch data science team in the electronics sector with our dedicated expertise in automatic text classification of multilingual customer reviews. In the context of this short engagement, LangTec’s top consultants will be tuning the client’s existing text classification solution to drive results to absolute high-end performance.

We are delighted to welcome Marc Ditschke to our team. Marc will support us as an intern on software systems development in the forthcoming six months. In his internship at LangTec he will be working on the functional extension of our team management software TeamTracker.

We are very pleased to have started the development of an innovative browser plug-in for a large online mail order company in the hardware and software sector. The plug-in will automatically answer requests for the approval or rejection of cookies or the collection of website usage data. Approval or rejection can be set either globally or for each domain individually. To implement this, the plug-in uses the same JavaScript APIs that Consent Management Platforms (CMP) use to manage cookie requests.