AI-Driven Legal Assistance: Optimizing Document Retrieval and Case Classification with NLP Techniques

Access to legal information is difficult, particularly for those who are unfamiliar with legal terminology. This research introduces an AI legal chatbot to improve document retrieval and case classification. The chatbot uses TF-IDF and cosine similarity to rank documents in order of relevance to user requests. It will classify instances so that users can navigate to the appropriate legal environment. The solution applies core NLP techniques, such as keyword extraction, to Elasticsearch, resulting in scalability and increased performance. That strategy produces better search results with a faster reaction time and could replace the old method of contacting lawyers. This study proposes constructing a scalable, simple, and low-complexity technique for easy access to legal resources.