Geniez AI, a startup developing a transformative framework that enables large language models (LLMs) and AI agents to seamlessly interact with mainframe data, has secured $6 million in seed funding. The round was led by StageOne Ventures and Canapi Ventures, with participation from a group of strategic angel investors. The company aims to bridge a critical gap in enterprise AI adoption by unlocking the vast troves of structured and historical data stored on legacy mainframe systems—often used by large financial institutions, government agencies, and industrial organizations. Despite the rise of generative AI, many enterprises still rely on mainframes for core operations, yet these systems remain largely inaccessible to modern AI tools due to technical incompatibility and security constraints. Geniez AI’s platform is designed to securely connect LLMs and AI agents to mainframe data without requiring extensive reengineering of existing infrastructure. By doing so, it enables organizations to leverage AI for tasks like automated reporting, real-time decision support, and intelligent data analysis—using data that has long been isolated from the AI revolution. The seed funding will be used to accelerate product development, expand the engineering team, and drive enterprise pilot programs with key clients in banking, insurance, and public sector industries. The company also plans to strengthen its security and compliance capabilities to meet the stringent standards required by regulated industries. “Mainframes are still the backbone of mission-critical systems, but they’ve been left behind in the AI wave,” said the company’s founder and CEO. “Our mission is to bring the power of AI to these systems—without compromising performance, security, or uptime.” With the rise of AI agents and autonomous workflows, the ability to integrate AI with legacy infrastructure is becoming a strategic imperative. Geniez AI positions itself at the forefront of this shift, helping enterprises modernize their AI capabilities while preserving their existing technology investments.