All you need to know about GenAI for Mainframe, in one easy place, from Geniez.
Hybrid Infrastructure AI
AI systems designed to operate seamlessly across mainframe, cloud, and distributed environments while respecting data locality and governance.
MIPS Optimization via AI
Using AI to analyze workloads and optimize execution patterns to reduce MIPS consumption and improve cost efficiency on IBM Z.
AIOps for IBM Z
Applying AI to automate and enhance IBM Z operations, including monitoring, incident response, performance optimization, and capacity forecasting.
Mainframe Skills Gap Mitigation
The use of AI to preserve institutional knowledge, assist less-experienced staff, and reduce dependency on scarce mainframe expertise.
Audit-Ready AI Insights
AI-generated outputs that include traceability, source attribution, and decision context to support regulatory and internal audits.
Mainframe AI Governance
Policies, controls, and oversight mechanisms that ensure AI usage on the mainframe is compliant, explainable, auditable, and aligned with enterprise risk standards.
AI Privacy Firewall for Z
A security layer that prevents sensitive or regulated mainframe data from being exposed to AI models, prompts, or external systems.
Vector Embeddings for Legacy Code
The conversion of legacy codebases (e.g., COBOL, PL/I) into vector representations that enable semantic search, similarity analysis, and AI reasoning.
Mainframe API Monetization (via AI)
Exposing mainframe capabilities and data through AI-driven APIs that enable new digital products, services, and revenue streams.
Cross-Platform AI Agents
AI agents capable of operating across mainframe, distributed, and cloud environments while maintaining contextual awareness and security boundaries.
Mainframe RAG (Retrieval-Augmented Generation)
A GenAI technique that retrieves relevant mainframe data, code, or documentation in real time to ground LLM responses in authoritative enterprise specific sources.
Zero-ETL for Mainframe
A data access approach where AI and analytics operate directly on mainframe data sources without duplication, transformation, or staging.
Z-Centric GenAI
A GenAI architecture designed around IBM Z as the system of record, rather than treating the mainframe as a peripheral data source.
Mainframe Data Democratization
Making mainframe data accessible to broader enterprise users and AI systems while preserving security, governance, and operational control.
Secure AI Gateway for Mainframe
A controlled interface that brokers AI access to mainframe data and systems, enforcing security, policy, rate-limiting, and auditability.
In-place AI Inference on z/OS
Executing AI inference directly within the z/OS environment, ensuring data never leaves the mainframe and maintaining maximum security and performance.
LLM with COBOL
The use of large language models to analyze, explain, modernize, test, or generate COBOL code while preserving business logic and system integrity.
Mainframe Semantic Search
AI-powered search that understands the meaning and context of mainframe assets—code, JCL, datasets, documentation—rather than relying on keyword matching.
Mainframe AI Ops
The application of AI and GenAI to automate, optimize, and predict mainframe operational activities such as incident resolution, workload balancing, and capacity management.
Big Iron / Maxicomputer / Mainframe Computer
High-performance, highly reliable enterprise computing systems—such as IBM Z—designed for mission-critical workloads, massive throughput, and extreme availability.
SMF Data Insights (GenAI)
The use of GenAI to analyze SMF (System Management Facilities) data for operational intelligence, capacity planning, performance tuning, and anomaly detection.
Mainframe AI Agent
An autonomous AI entity that understands mainframe data, applications, and operational context, capable of executing tasks, answering questions, and orchestrating workflows.
RACF-Controlled AI Security
AI access governance enforced through RACF policies, ensuring all AI interactions comply with existing mainframe authentication, authorization, and audit controls. (Also applicable to ACF2 and Top Secret)
Real-time Mainframe Data Access
The ability for AI systems to query and consume live mainframe data as it changes, without batch delays or replication.
zIIP-Optimized AI
AI workloads designed to offload processing to IBM Z Integrated Information Processors (zIIPs), reducing general-purpose MIPS consumption and lowering operational costs.
No-ETL Data Streaming
Direct, continuous access to mainframe data without extract-transform-load pipelines, preserving data fidelity and minimizing latency and risk.
Mainframe LLM Integration
The secure connection of large language models (LLMs) with mainframe environments (e.g., IBM Z) to enable natural-language interaction, analysis, and automation directly on core systems.
Cookie Settings
By clicking “Accept All Cookies”, you agree to the storing of cookies on your device to enhance site navigation, analyze site usage and assist in our marketing efforts.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
We use cookies and similar technologies to help personalise content, tailor and measure ads, and provide a better experience. By clicking OK or turning an option on in Cookie Preferences, you agree to this, as outlined in our cookie Policy.
