  The intent recognition is an essential algorithm of any conversational AI
application. It is responsible for the classification of an input message into
meaningful classes. In many bot development platforms, we can configure the NLU
pipeline. Several intent recognition services are currently available as an
API, or we choose from many open-source alternatives. However, there is no
comparison of intent recognition services and open-source algorithms. Many
factors make the selection of the right approach to the intent recognition
challenging in practice. In this paper, we suggest criteria to choose the best
intent recognition algorithm for an application. We present a dataset for
evaluation. Finally, we compare selected public NLU services with selected
open-source algorithms for intent recognition.
