Large language models are insufficiently adapted to the needs of German SMEs. The goal of the project is to develop methods and a framework for the efficient adaptation of language models for SME-specific applications. In the BHT subproject, data- and model-centric approaches will be explored and prototypically tested for three use cases: (1) automated text authoring for the finance industry, (2) document matching for legal tech companies, and (3) improved reading order recognition in legal and finance documents.


  • Merantix Labs GmbH 2txt NLG GmbH
  • Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V. (IAIS)
Associated Partners:
  • Aleph Alpha
  • Börsenmedien AG
  • briink GmbH
  • caralegal GmbH
  • finanztreff GmbH
  • hessian.AI
  • KI Bundesverband
  • K.I.E.Z
  • L-One Systems GmbH
Funded by:

BMBF - KI in Unternehmen

Contact at the BHT:

Prof. Dr. Alexander Löser

Prof. Dr. Peter Tröger