We are in the process of developing a system where through Natural Language Processing we are analyzing and interpreting the judgement and orders of the Court vis a vis the case. This will help in identifying the similarities based on various factors such as legal issues, factual circumstances, and judicial reasoning etc. It will help in bringing more transparency, accountability, and bias mitigation, prevent misuse of the legal system, increase efficiency, as well as last but not least speed in the judicial system.

Though it is a challenging task, therefore, we have utilized automation tools and semi-supervised and unsupervised learning algorithms. It helps us in streamlining the process, simplifying the structure of the cases and extraction of common features that form the basis of a litigation. In this process the cases with procedural and technical flaws are taken separately.

However, before implementing AI based system the challenges we have faced at different levels i.e. Data Collection, Topics / Domain analysis, Preprocessing i.e. tokenization, lemmatization etc. Before identifying the similarities, extraction of features was quite important and we have utilized deep learning techniques like BERT (Bidirectional Encoder Representations from Transformers) etc.

The process of Validation and Evaluation is in progress and the outcome will again be fed into the system to increase the accuracy with respect to the relevance and similarity to the target case. Additionally, evaluate the performance of the AI system using standard evaluation metrics such as precision, recall, and F1-score.

It’s important to note that developing an effective AI system for court order similarity analysis requires expertise in both NLP techniques and legal domain knowledge. Therefore, we have undertaken this complex task. Additionally, ensuring the system’s compliance with legal and ethical standards, including data privacy and confidentiality, is crucial throughout the development and deployment process.