AI on IBM Z

Unlock real-time AI insights with IBM Z

AI on IBM Z® brings real-time insights by applying machine learning directly to transactional data—eliminating the need for data movement.

Leveraging the advanced hardware and software stack of IBM z17, businesses can scale multiple AI models to power predictive use cases such as fraud detection and retail automation. With high throughput, low latency, and industry-leading cyber-resilience, IBM Z is built for mission-critical AI.

Discover AI in banking automation

Speed to scale with transaction volume

With IBM z17, process up to 450 billion inference operations per day with 1 ms response time for real-time use cases.¹

Get real-time insights when needed

Infuse AI into every transaction—no data movement—while meeting the most stringent SLAs and response times.

Increased inference throughput

Route inference requests to any idle Integrated Accelerator for AI to boost throughput up to 7.5x over IBM z16.²

Keep data secure and compliant

Run AI where your data already resides to safeguard sensitive information and support regulatory compliance.

Featured products

Unlock the potential of generative AI with IBM watsonx Code Assistant for Z and watsonx Assistant for Z . These tools enable hybrid or on-premise AI solutions, with future capabilities planned through the Spyre Accelerator³—expanding the reach of AI across your enterprise infrastructure.

Generative AI

A generative AI-powered tool that provides an end-to-end application developer lifecycle. It includes application discovery and analysis, automated code refactoring and COBOL to Java conversion.

IBM watsonx Code Assistant for Z

AI Toolkit

Consists of IBM® Elite Support and IBM Secure Engineering. These vet and scan open-source AI, serving frameworks and IBM-certified containers for security vulnerabilities, and validate compliance with industry regulations.

AI Toolkit for IBM Z

AI fixed into real-world applications

An AI solution for users to build machine learning models by using any platform of choice and deploy those models within transactional applications while maintaining SLAs.

Machine Learning for IBM z/OS

Artificial training data

A family of artificially generated datasets designed to enhance predictive AI model training and LLMs to benefit IBM Z enterprises in financial services to gain quick access to relevant and rich data for AI projects.

IBM Synthetic Data Sets

Related products

Conversational AI

IBM watsonx Assistant for Z delivers secure, AI-powered virtual agents at scale on IBM Z for smarter customer interactions.

AI-infused transactional data

IBM Db2 for z/OS powers secure, agile data serving for hybrid cloud, transactional, and analytics workloads.

Python AI Toolkit

The Python AI Toolkit for IBM z/OS gives you key open-source tools to run AI and ML workloads on IBM Z.

Accelerate TensorFlow Inference

IBM ZDNN Plug-in for TensorFlow lets you deploy AI models near your core apps on IBM Z using the Integrated Accelerator for AI.

In-memory computing performance

IBM Z Platform for Apache Spark supports fast in-memory analytics using Java, Scala, Python, and R on IBM Z.

Compile .onnx deep learning AI models into shared libraries

IBM Z Deep Learning Compiler runs ONNX AI models on IBM Z with low dependency using the Integrated Accelerator for AI.

Popular open source tools

Anaconda on IBM Z and LinuxONE runs Scikit-learn, NumPy, and more in zCX containers for efficient data science.

Demo video

Anti-Money Laundering: Unmasking Money Laundering in real-time on IBM z17

Discover how a multiple AI model approach accelerates Anti-Money Laundering (AML) on IBM z17 and drives accuracy improvements to detect illicit activity, simplify regulatory compliance, and safeguard economic transparency.

Resources

How mainframes are rewriting the AI playbook

Learn about the key elements of current and next-generation mainframes and how they are transforming the AI landscape.

Mainframes as mainstays of digital transformation

Discover how mainframes are more relevant than ever for hybrid cloud optimization, AI innovation, and digital transformation.

Optimized inferencing and integration with AI on IBM Z

Learn how to enable AI solutions in business-critical use cases, such as fraud detection and credit risk scoring, on the platform.

What if IBM Z could help stop fraud?

Discover low-latency AI on a highly trustworthy and secure enterprise system: the modernized IBM Mainframe.

Take the next step

Discover how to use AI and machine learning to convert data from every transaction into real-time insights.

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Footnotes

¹ DISCLAIMER: Performance result is extrapolated from IBM® internal tests running on IBM Systems Hardware of machine type 9175. The benchmark was executed with 1 thread performing local inference operations using a LSTM based synthetic Credit Card Fraud Detection model (https://github.com/IBM/ai-on-z-fraud-detection) to exploit the Integrated Accelerator for AI. A batch size of 160 was used. IBM Systems Hardware configuration: 1 LPAR running Red Hat® Enterprise Linux® 9.4 with 6 IFLs (SMT), 128 GB memory. 1 LPAR with 2 CPs, 4 zIIPs and 256 GB memory running IBM z/OS® 3.1 with IBM z/OS Container Extensions (zCX) feature. Results may vary.

² DISCLAIMER: Performance results are based on internal tests exploiting the IBM Integrated Accelerator for AI for inference operations on IBM z16 and z17. On IBM z17, each IBM Integrated Accelerator for AI allows any CPU within a drawer to direct AI inference request to any of the 8 idle AI accelerators on the same drawer. The tests involved running inference operations on 8 parallel threads with batch size of 1. Both IBM z16 and z17 were configured with 2 GCPs, 4 zIIPs with SMT and 256 GB memory on IBM z/OS V3R1 with IBM Z Deep Learning Compiler 4.3.0, using a synthetic credit card fraud detection model (https://github.com/IBM/ai-on-z-fraud-detection). Results may vary.

³ Upon Spyre Accelerator availability. The IBM Spyre Accelerator is current in tech preview. https://www.ibm.com/docs/en/announcements/z17-makes-more-possible