Ayushi Kukreja

Architected and implemented an AI-powered Legal Analytics Platform using advanced NLP techniques for case file analysis. Engineered a high-performance RAG system with FAISS vector store for legal document Q&A. Enhanced Named Entity Recognition (NER) by fine-tuning the OpenNYAI model for better accuracy. Developed a Relation Extraction pipeline using Mixtral LLM to create structured knowledge tuples. Designed and implemented a scalable Knowledge Graph with Neo4j for legal relationship mapping. Created a Natural Language to Cypher Query system for advanced legal insights. Integrated MACT API to automate court-mandated legal compensation calculations. Implemented text summarization models for improved legal case file accessibility. Fine-tuned Meta's M2M100 model for accurate multi-lingual legal document translation.

Delivered over 100 timely and precise solutions to computer science inquiries on the Chegg platform, highlighting a deep understanding of the subject matter. Delivered clear and concise explanations to aid students in comprehending complex concepts in programming, algorithms, data structures, and various computer science subjects.

Contributed to the development and upkeep of the foundation’s website, ensuring a seamless user experience and visually engaging interface for over 50 unique visitors per day. Optimized site compatibility across devices and screens, resulting in a 20% traffic boost. Tech Stack – HTML, CSS, JavaScript, jQuery