  In recent years, the field of Legal Tech has risen in prevalence, as the
Natural Language Processing (NLP) and legal disciplines have combined forces to
digitalize legal processes. Amidst the steady flow of research solutions
stemming from the NLP domain, the study of use cases has fallen behind, leading
to a number of innovative technical methods without a place in practice. In
this work, we aim to build a structured overview of Legal Tech use cases,
grounded in NLP literature, but also supplemented by voices from legal practice
in Germany. Based upon a Systematic Literature Review, we identify seven
categories of NLP technologies for the legal domain, which are then studied in
juxtaposition to 22 legal use cases. In the investigation of these use cases,
we identify 15 ethical, legal, and social aspects (ELSA), shedding light on the
potential concerns of digitally transforming the legal domain.
