Geniez AI

What Geniez AI does

Geniez AI provides a Generative AI Framework that enables secure, efficient, and auditable real-time mainframe data access using natural language. It connects Large Language Models (LLMs) and AI agents to mainframe data sources without requiring data replication, ETL, or CDC. The platform offers tools for AI agents and application development built on a secured real-time mainframe data access framework. It aims to increase productivity, reduce downtime, and improve observability for mainframe operations, security, and software development teams by transforming complex mainframe data into actionable intelligence through natural language queries. The framework runs on zIIP engines and leverages native mainframe security controls.

Products

• Geniez GenAI FrameworkEnables secure, efficient, and auditable real-time mainframe data access using natural language, connecting LLMs and AI agents to mainframe data without prerequisites and installing in hours.
• Operations GenieA curated AI agent designed to assist mainframe operations professionals by allowing them to query SMF, OPERLOG, and other system logs in natural language, troubleshoot system issues, and perform health checks.
• Software Development GenieEnables mainframe developers to run jobs, troubleshoot ABENDs and JCL errors, get fix suggestions, review job output, and query DB2, all within their code assistant screen, eliminating context switching.
• Geniez GenAI Mainframe DatabotRuns on zIIP engines and leverages Telum II processor and Spyre accelerator to efficiently retrieve real-time data from popular data sources like DB2, IMS, MQ, RACF, VSAM, and COBOL-mapped data sets.
• Geniez GenAI Framework – Security SMGLeverages the latest AI models for fast mainframe security review at scale, including parmlib configuration, RACF settings, source code vulnerability scanning, and audit reviews.

Key capabilities

• Real-time direct access to any mainframe data source
• Patented technology relying strictly on mainframe security controls
• No prerequisites, installs in hours
• Mainframe optimized software running on zIIP engines
• Web UI provides debugging, observability, audit and administration capabilities
• Support any LLM and AI agent on premises or in the public cloud
• Eliminates context switching between IDE and 3270 screens
• Complete job lifecycle management from the IDE
• Leverage standard AI protocols (MCP, A2A)
• Secured by mainframe permissions
• Accessing data at its source
• All data available for AI
• No need for data replication, ETL and CDC
• Security-first patent-pending design
• Authenticates using securely generated API tokens mapped to real mainframe user IDs
• Access controlled via the mainframe’s native access control system
• No need to train models in advance, data is retrieved in real-time
• Data access relying on native z/OS interfaces, no additional software products required
• Software-only solution, no special hardware required

Use cases

• Compare two timeframes
• Check current system activity
• Explain what a job is doing
• Troubleshoot system issues
• Query SMF in natural language
• Query databases in natural language
• Perform system healthchecks
• Extend AI code assistants with mainframe capabilities
• Enrich enterprise AI applications with mainframe insights
• Troubleshoot ABENDs and JCL errors
• Get fix suggestions for code
• Review job output
• Query DB2 from IDE
• Connect AI applications (digital assistants) with real-time mainframe data
• Synthesize, summarize, and generate actionable knowledge from mainframe operations data
• Proactively check for vulnerabilities
• Analyze audit records and verify compliance
• Generate and explain code
• Compile programs and run test jobs
• Check other data sets and look at source members
• Improve customer experience by connecting GenAI to real-time mainframe data
• Find data in mainframe systems (needle in a haystack)
• Querying SMF in natural language for troubleshooting
• Searching OPERLOG/SYSLOG for errors, root cause, anomalies, and optimizations
• Analyzing job output logs to determine execution status, explain failures, and suggest remediation
• Comparing settings in high-availability (HA) CICS/DB2 configurations
• Detect anomalies and understand system behavior
• Diagnosing and resolving database issues for DBAs
• Enhance security management with speed and precision
• Strengthen capacity planning by analyzing historical utilization patterns
• Checking for vulnerabilities using system management tools (SMP/E)
• Identifying anomalies and changes in permissions (RACF, SMF audit records)
• Audit and compliance reporting for security auditors
• Understanding compilation errors and suggesting fixes
• Checking errors in job output for failed jobs
• Searching for data sets and source members
• Analyzing programs and checking for active COBOL programs
• Security vulnerability testing of real-time mainframe data, code, and configurations
• Reviewing Parmlib configuration (APF, SVC, PPT, LPA, AUTH TSO/E)
• Reviewing RACF settings (configuration and permission chains)
• Source code vulnerability scanning (COBOL, ASM, PL/I)
• Anomaly detection based on RACF, MVS, TCP/IP SMF records

AI approach

Geniez AI connects Large Language Models (LLMs) and AI agents to real-time mainframe data sources, enabling natural language queries for mainframe operations, security, and software development. It provides a framework for secure, efficient, and auditable access to mainframe data, without requiring data replication or specialized mainframe skills. The platform supports various LLMs and AI agents, on-premises or in the public cloud, and leverages mainframe-optimized software running on zIIP engines.

Tech named: LLMs, AI agents, Generative AI, Telum II processor, Spyre accelerator

What it says sets it apart

• Connects LLMs and AI agents to real-time mainframe data
• No prerequisites, installs in hours
• Patented technology relying strictly on mainframe security controls
• Mainframe optimized software running on zIIP engines
• Eliminates need for data replication, ETL, and CDC
• Provides real-time insights from mainframe data
• Supports any LLM and AI agent (on-prem or public cloud)
• Reduces context switching for developers (IDE integration)
• Founders have a proven track record in mainframe innovation (built Model9)
• Startup-speed innovation for the mainframe market
• Security-first patent-pending design with native mainframe security integration
• No need to train models in advance
• Data access relies on native z/OS interfaces
• Software-only solution, no special hardware required

Funding rounds we track

From the AI funding tracker — rounds as reported by the linked publications.