Mainframes run many significant commercial applications and are a key part of strategic investments for digital transformation, hybrid cloud computing, APIs, and, more recently, a rapidly growing number of generative AI and agentic AI projects.
Organizations place new demands on mainframes every day, such as more quickly processing increasing amounts of low value credit card transactions or delivering cash from ATMs anywhere in the world. Generative AI projects are related because they fundamentally depend on the quality of data available to them.
Modern mainframe systems are more than capable to meet these new AI related demands. New hardware and operating system releases bring speed, flexibility, and power. Database updates improve latency, connectivity, reliability, and resiliency.
Why Mainframe Data is So Valuable
Mainframes operate in tightly controlled environments, making them the most secure, reliable and efficient platforms for processing business transactions and persisting the resulting data.
Tightly controlled access to computing resources such as memory, disk, and CPU reduce the chances of transaction failure, and improves the ability to roll back when one does fail, automatically preserving data consistency and integrity.
The value of such data increases significantly as organizations invest in generative AI and agentic AI systems for enhancing productivity and service levels. Transactional mainframe data is a veritable gold mine for AI model training and fine tuning.
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