Legal Buddy

Today’s litigators are expected to quickly make well-informed decisions and develop strong strategies and a big-picture perspective. To accomplish these goals in shorter time frames, we present Legal Buddy to streamline the document review and analysis process. Legal Buddy gives attorneys more time for strategic planning by providing a report with an overview of the case, a liability analysis, a case analysis, applicable laws and defenses, damages, and recommendations for the case. The attorney (user) can upload medical records or summaries, witness statements, deposition transcripts or summaries, pleadings, and other legal documents, notes, or summaries and the system will use Upstage's Document OCR to extract text from the documents. Then, the Llama model summarizes all the text and the text is given to the OpenAI's o1 LLM to generate a liability analysis and report. Additionally, we stored a data set of U.S. case law on MongoDB using LlamaIndex and enabled a vector search to find the relevant cases for the case analysis feature. The system matches information from our specific case from the uploaded documents with other cases from the data set of U.S. case law. OpenAI's o1 reasoning is used to generate case analysis and the case analysis is included in the report. There is currently a resource limit on the length of the documents that can be uploaded and the amount of cases that can be stored, so for now we are uploading summaries of legal documents instead of the actual documents and the data set we are storing is a sub-set (about 500 cases) of the entire U.S. case law data set. We would like to have more processing and storage functionality, but that just wasn't feasible for this hackathon. For the future, we would like the user to interact with live data from a data source (i.e. Westlaw, LexisNexis) instead of a data set. We would also like the user to query case information through a chat interface.