  Legal research is a crucial task in the practice of law. It requires intense
human effort and intellectual prudence to research a legal case and prepare
arguments. Recent boom in generative AI has not translated to proportionate
rise in impactful legal applications, because of low trustworthiness and and
the scarcity of specialized datasets for training Large Language Models (LLMs).
This position paper explores the potential of LLMs within Legal Text Analytics
(LTA), highlighting specific areas where the integration of human expertise can
significantly enhance their performance to match that of experts. We introduce
a novel dataset and describe a human centered, compound AI system that
principally incorporates human inputs for performing LTA tasks with LLMs.
