Agentic Understanding and Retrieval Architecture

The Agentic Understanding and Retrieval Architecture (AURA) group focuses on advancing cutting-edge research across the following key domains:

• Development and fine-tuning of private large language models (LLMs) for secure and efficient NLP applications

• Implementation of state-of-the-art natural language processing algorithms leveraging LLMs

• Integration of retrieval-augmented generation (RAG) techniques to enhance long-term memory and context retention

• Research and deployment of agentic AI systems capable of autonomous decision-making and multi-turn dialogue management

• Design and development of domain-specific intelligent agents, including conversational chat-bots, healthcare advisors, and legal assistance systems

• Optimization of LLM-based architectures for privacy, scalability, and real-time inference