Current Generative AI (GAI) models face significant challenges when adapted and applied in DoD contexts, including the inability to access proprietary or classified data, reliance on pre-existing training data that may be outdated or unreliable, a lack of scalability, and inherent model bias. These models also often require substantial computational resources to function effectively, which limits their deployment in edge-computing scenarios where power and processing capabilities are constrained. KrakenAI is a groundbreaking Large Language Model (LLM) and conversational AI solution specifically designed to support cybersecurity analysts, particularly those operating in remote, bandwidth-limited regions. Through a Question & Answer and summarization-optimized LLM, KrakenAI uniquely addresses the dual needs of keeping analysts updated on evolving threat patterns and vulnerabilities while providing decision-making support to aid in defense and mitigation responses. Built on a sophisticated 70-billion parameter model, KrakenAI leverages layered model training which combines relevant cybersecurity datasets from Open-Source Intelligence (OSINT), Publicly Available Information (PAI), and classified sources to create highly specialized models, understand complex queries, and provide accurate responses, even without continuous internet access. These models are finely tuned to mission-critical requirements, ensuring that KrakenAI remains agile and capable of delivering real-time, actionable insights. In the cybersecurity domain, KrakenAI leverages datasets such as the MITRE ATT&CK framework, which enhances its predictive capabilities for identifying and mitigating evolving threats. By staying current with adversarial tactics, techniques, and procedures, KrakenAI ensures it is always contextually relevant for national security purposes. Its domain-specific adaptability means KrakenAI evolves alongside adversarial advancements, offering a future-proof solution to rapidly changing security challenges.