JAVIS: A Comprehensive AI System Designed for Innovation and Research in Healthcare

Language models have significant potential to improve clinical workflows, accelerate research, and enhance patient care in hospitals. However, privacy constraints, limited compatibility with diverse IT systems, and the absence of a holistic approach for managing language models within internal networks hinder broader adoption. JAVIS tackles these challenges by offering a secure, scalable, and modular framework for Large Language Models (LLMs) and Vision-Language Models (VLMs), fully operating on private hospital networks. Its features include high-throughput data labeling (text, images, and audio), a no-code LLM training interface, an auto-labeling module for named entity recognition (NER) tasks, and distributed deployment of LLMs and VLMs on multi-GPU infrastructures that provide an internal network chat service. This poster outlines JAVIS's architecture, key features, and results demonstrating robust performance in data labeling, training, and large-scale inference.