TLDR: Geniez AI has successfully raised $6 million in seed funding, co-led by StageOne Ventures and Canapi Ventures. This capital will be used to advance its innovative framework that connects large language models (LLMs) and AI agents directly with real-time mainframe data. The technology aims to enable sophisticated AI-driven analysis and automation for enterprises, enhancing customer experiences and operational efficiency without the need for costly data migration.
NEW YORK – Geniez AI, a pioneering company focused on integrating cutting-edge artificial intelligence with traditional mainframe systems, announced today that it has secured $6 million in seed funding. The investment round was co-led by prominent venture capital firms StageOne Ventures and Canapi Ventures, signaling strong confidence in Geniez AI’s unique approach to enterprise modernization.
The funding will be instrumental in scaling Geniez AI’s engineering and go-to-market teams, expanding strategic partnerships within the enterprise technology sector, and fostering deeper integration with leading Generative AI platforms.
Geniez AI’s core offering is a groundbreaking framework designed to seamlessly connect large language models (LLMs) and AI agents with real-time data residing on mainframes. This innovative solution addresses a critical challenge faced by many large enterprises, particularly in sectors like finance, insurance, retail, government, and healthcare, where mainframes continue to house vast amounts of mission-critical, up-to-date transactional and historical data.
According to Gil Peleg, Co-founder and CEO of Geniez AI, “Mainframes are at the heart of the global economy, holding the most up to date transaction data as well as decades of historical data which are extremely valuable for AI.” He further elaborated, “We’re giving enterprises the best of both worlds: the power and trust of the mainframe with the innovation and velocity of the AI ecosystem.”
The Geniez AI framework operates natively on the mainframe, ensuring secure and efficient data access. It leverages standard Generative AI protocols, such as the Model Content Protocol (MCP), to facilitate real-time data access for LLMs and AI agents, whether they are running on-premises or in public cloud environments like OpenAI ChatGPT, Anthropic Claude, or Meta Llama. This capability allows businesses to unlock the full potential of their mainframe data, enabling sophisticated AI-driven analysis, automation, and intelligent decision-making without the need for extensive data migration or significant infrastructure modernization costs.
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This integration is expected to empower enterprises to enhance customer experiences, improve operational efficiency, and generate new revenue streams by bringing their most critical systems into the future of AI.
