3P
3rd Party Support
IBM · IBM AI Optimizer for z/OS → Azure Machine Learning · Migration

Your Trusted Path for IBM AI Optimizer to Azure ML Migration

We migrate IBM AI Optimizer for z/OS to Azure Machine Learning via fixed-scope projects. Senior engineers manage Db2, RACF, and compliance while your legacy environment stays under support.

Get My Free AssessmentGet a fixed-scope proposal from senior engineers.

Get My Free Assessment

Get a fixed-scope proposal from senior engineers.

Your quote will be sent to this address.

By submitting this form, you agree to our Privacy Policy.

Powered by the 3PS Migration Engine

The lowest-cost way off IBM AI Optimizer for z/OS: our migration tooling automates the repetitive work —you pay senior engineers for judgment, not keystrokes.

Automated discovery
Your IBM AI Optimizer for z/OS estate mapped — workloads, dependencies, licensing — before day one
Conversion tooling
Schema, config and workload translation to Azure Machine Learning, automated where it's safe
Parity validation
Side-by-side testing proves Azure Machine Learning matches production before cutover
Runbook cutover
Rehearsed, reversible, scheduled in your maintenance window
40-70% vs vendor ren
Savings on legacy support
6-9 months with 3-5
Typical migration timeline
$180,000–$1,200,000
Typical project budget

How we support IBM AI Optimizer for z/OS → Azure Machine Learning after migration

  • Fixed-scope migration by senior platform engineers
  • Your legacy AI Optimizer stays under vendor support
  • Save 40-70% on legacy support renewals
  • 24/7 US-based post-migration Azure ML support
  • Concurrent pipeline build eliminates project gaps
  • Proven Db2 and RACF integration process

Cloud mandate pressure

Enterprise cloud mandates favoring Microsoft Azure force a move off mainframe AI, but you lack Azure ML migration expertise.

IBM ELA renegotiation risk

Impending IBM Enterprise License Agreement renegotiations make legacy support costs unpredictable and could trigger budget crises.

Mainframe ML skills gap

Your legacy mainframe team cannot support modern ML frameworks, creating a skill gap that delays innovation and increases operational risk.

IBM AI Optimizer for z/OS → Azure Machine Learning migration — your questions answered

How do you handle Db2 for z/OS stored procedure integrations?+

We assess your existing Db2 stored procedures and rebuild them as Azure ML pipelines or SQL Server equivalents, ensuring functional parity and data lineage.

What about RACF security credential mapping to Azure AD?+

During migration, we map RACF user identities to Azure Active Directory (Entra ID) roles and configure credential vaults. No security gaps occur.

Can I keep IBM support while migrating?+

Yes, as long as your IBM vendor contract is active. If it lapses, our third-party support covers most operational issues on the legacy platform while you complete the move.

How does this help with regulatory requirements on data residency?+

We deploy Azure ML in your chosen regions and configure policies for data residency and encryption. Our team has experience with financial services regulatory frameworks.

Your IBM AI Optimizer to Azure ML Migration Starts Here

Concurrently support your existing AI Optimizer environment while building the Azure pipeline. Our managed services include Azure ML model monitoring, automated retraining pipelines, and integration with Azure Sentinel for audit logging.

Get a Quote

Your quote will be sent to this address.

By submitting this form, you agree to our Privacy Policy.