Legal systems involve complex procedures and technical language that are difficult for common users to understand. Existing systems provide unstructured court updates without a clear procedural flow. This paper proposes an AIdriven legal intelligence platform that applies Natural Language Processing (NLP) and Machine Learning (ML) to understand userdescribed legal cases. The system automatically identifies relevant legal sections, assesses risk and urgency, converts court summaries into structured timelines and decision flowcharts, and recommends suitable advocates. Automated analysis reduces manual effort and dependency on repeated legal consultations while enhancing transparency and efficiency in judicial case understanding.
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