HSAAI: A Sovereign, Self-Hosted Enterprise AI Platform for Secure RAG, Agentic Workflows, and AI Governance

HSAAI is a sovereign, self-hosted Enterprise Artificial Intelligence platform designed to provide organizations with secure and governed access to large language models, Retrieval-Augmented Generation (RAG), AI agents, enterprise knowledge, observability, and cloud-native infrastructure while maintaining control over sensitive data and AI operations. This paper presents the architecture, design principles, research questions, and evaluation framework of HSAAI. The platform integrates enterprise RAG, agentic and multi-agent workflows, AI governance, identity and access control, security, LLMOps/MLOps, observability, and containerized deployment within a unified enterprise AI architecture. Particular attention is given to data sovereignty, controlled agent execution, policy enforcement, auditability, self-hosted deployment, Arabic-English enterprise AI, and operational resilience. The paper also defines an empirical evaluation methodology covering retrieval quality, factual faithfulness, agent task success, security-policy enforcement, system performance, reliability, and bilingual enterprise workloads. HSAAI is presented as an engineering and research platform for studying secure, sovereign, governed, and agentic artificial intelligence in enterprise environments. The associated source-code repository and technical artifacts are publicly available through the HSAAI GitHub project.