  Artificial Intelligence techniques are already popular and important in the
legal domain. We extract legal indicators from judicial judgment to decrease
the asymmetry of information of the legal system and the access-to-justice gap.
We use NLP methods to extract interesting entities/data from judgments to
construct networks of lawyers and judgments. We propose metrics to rank lawyers
based on their experience, wins/loss ratio and their importance in the network
of lawyers. We also perform community detection in the network of judgments and
propose metrics to represent the difficulty of cases capitalising on
communities features.
