Designed an AI-driven prediction service that analyzes historical legal cases and user-provided case details to estimate potential outcomes. The system combines structured case data with LLM-generated insights to produce prediction scores and supporting explanations, helping users evaluate their cases before initiating legal proceedings.
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Developed an AI-powered HR assistant using Retrieval-Augmented Generation (RAG) to provide accurate, context-aware answers from company policy documents. Implemented document ingestion, embedding generation, semantic search, and LLM-based response generation, enabling employees to retrieve relevant HR information quickly through natural language queries.
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Built and maintained the backend of a cloud-based Alternative Dispute Resolution (ADR) platform that streamlines legal case management. Designed scalable REST APIs, implemented secure authentication and RBAC, integrated third-party services including QuickBooks Online, Zoom, and Brevo, and developed asynchronous workflows using Redis queues. Improved system performance through database optimization and modular architecture while supporting document management, billing, and notification services.