How Google Cloud and Sapient Slingshot help enterprises understand, interpret and safely transform legacy systems.
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Mainframe systems sit at the core of the enterprise, but they remain some of the least understood.
They process payments, calculate risk, manage claims and reconcile ledgers. Many were written decades ago. Some still run on COBOL. All of them encode years—sometimes decades—of institutional knowledge shaped by regulatory change, product evolution and operational realities.
These systems are not just legacy infrastructure. They are critical business logic, which are deeply embedded, highly interdependent and difficult to interpret.
This is why mainframe modernization has consistently stalled.
Not because of infrastructure limitations but because of a lack of understanding.
Modernization has long been framed as an infrastructure problem:
Traditional approaches relied heavily on manual code analysis and SME knowledge. At enterprise scale, this approach is slow, inconsistent and difficult to sustain—and prone to error, where defective software could have a serious negative impact on business operations. Business logic remains fragmented across programs, batch jobs and interfaces—while documentation is often incomplete or outdated.
This is the gap modernization has never solved: understanding before modernization.
Google Cloud, through Vertex AI and foundation models such as Gemini, introduces a fundamentally new capability: the ability to analyze and reason over large, complex codebases within a secure enterprise environment.
This is not about generating new code faster. It is about understanding existing systems with precision.
At scale, this enables organizations to:
Critically, this analysis happens within a secure Google Cloud Platform (GCP) tenancy—addressing concerns around intellectual property, data sovereignty and regulatory compliance.
For the first time, enterprises can “see” their mainframe systems clearly before attempting to change them.
This is where Sapient Slingshot, an AI software development platform, plays a critical role.
Operating within GCP environments, Slingshot transforms AI-driven analysis into delivery-ready outputs by:
The result is not just insight but controlled, scalable execution.
This distinction is architectural:
Together, they address both sides of the modernization equation: understanding and execution—with Publicis Sapient recognized by Google Cloud as a mainframe modernization partner across application transformation, mainframe migration and cloud-native modernization.
Once system behavior is understood and operationalized, modernization becomes intentional.
Instead of simply relocating applications, organizations can redesign them for cloud-native environments using:
What makes this different is the combination of AI-driven system understanding and structured execution.
In a recent engagement with a large retail and commercial U.K. bank, this combined Google Cloud and Sapient Slingshot approach was applied to analyze and document core banking feeds under strict operational resilience requirements. This included hundreds of interdependent batch processes built on COBOL-based mainframe logic, with limited documentation and heavy reliance on SME knowledge—making traditional, manual code-to-spec analysis both slow and high risk.
Using Vertex AI and Gemini within Google Cloud, alongside Slingshot’s structured delivery layer, the team analyzed over 200+ programs and 300+ feeds—processing nearly half a million lines of code. This enabled rapid extraction of business rules, dependencies and data mapping into traceable reviewable specifications.
The result was a 70 to 85 percent reduction in manual effort, analysis timelines reduced from weeks to days and a 95 percent accuracy in specifications—all while maintaining full traceability to source code. Most importantly, the program restored confidence in scaling modernization safely across the estate.
For years, core modernization has been constrained by uncertainty.
Enterprises were forced to choose between leaving legacy systems untouched or taking on significant transformation risk.
The tradeoff is no longer necessary. By combining Google Cloud’s AI-powered analysis and secure infrastructure with Slingshot’s structured execution and lifecycle orchestration, organizations can move from guesswork to clarity and from risk to controlled transformation.
Mainframe modernization is no longer a leap of faith. It is a disciplined, AI-enabled process.
Register for our upcoming webinar to see how AI-powered analysis and structured execution are accelerating mainframe modernization.