BRQ and AWS

Legacy and mainframe modernization

Modernize your legacy without stopping the business

Cut costs, speed up launches and prepare your critical systems for the next decade. Portfolio assessment, agentic AI and governed execution.

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  • -2.5x

    OPEX in a real case

  • AWS competencies in Mainframe Modernization and Generative AI

Why now

The mainframe isn't the problem. Inertia is.

  • 250 bn

    lines of COBOL in production worldwide

  • 70%

    of global banking transactions run on mainframe

  • 90%

    of credit card transactions do too

  • 55-58

    average age of a COBOL programmer, with 10% retiring every year

The mainframe isn’t a thing of the past. After years of treating it as legacy to be discarded, it has become clear that leaving the platform hastily is costly.

Today’s priority is different: reduce technical debt and prepare critical systems for the next decade, wherever they run best.

  • Inertia has a cost.

    Keeping legacy systems in “maintenance mode” builds up technical debt and competitive disadvantage.

  • A hasty exit fails.

    Poorly planned migrations cause disruption, delays and financial loss.

  • The path that works.

    Modernize with method: assess the portfolio and decide, workload by workload, what evolves and how.

Challenges

The challenges that make modernization hard

Modernizing critical systems without a method is risky. Most failed projects share the same root cause: the application portfolio was never properly assessed, and resources were underestimated.

  1. Assessing the application portfolio to decide what to modernize and how.
  2. Modernizing the core without disrupting operations or affecting the customer experience.
  3. Going beyond code translation: handling architecture, integration, compliance, resilience and disaster recovery.
  4. Accelerating with AI and agents without losing control and traceability.
  5. Securing and retaining expertise in legacy and mainframe systems, the scarcest resource in the market.

Our method

An end-to-end journey, from diagnosis to operations

Diagnosis feeds the plan, the plan guides execution, and execution sustains operations. Four linked phases, each with its own deliverables and a clear outcome for the client, so modernization advances in waves, with no rework between stages and no disruption to what is already live.

Outcome for the client

A clear picture of the legacy estate and the decision, workload by workload, of what to modernize and which standard to apply. This is the phase that does the most to prevent failed projects.

What we do in this phase

  • Assessment of the legacy environment (mainframe, VMware and critical workloads)
  • TCO analysis and migration scenario modeling
  • Roadmap definition aligned with AWS MAP

AWS competencies

Mainframe: the most critical legacy, with the most recognized partner

  • Mainframe Modernization

    We are the first partner in Latin America to earn the AWS Mainframe Modernization competency, audited and recognized by AWS, with more than 100 legacy specialists.

    Standard per workload

    We assess each workload and apply the right standard: replatform, refactor into modern architectures, or redesign.

  • Generative AI

    We earned the AWS Generative AI competency: an AWS-audited validation of our expertise in designing and delivering generative AI solutions safely and with governance.

    Responsible use of AI

    In modernization, this competency underpins the responsible use of agentic AI and gives clients the assurance of a partner vetted by AWS itself to lead AI projects.

Journey with AWS incentives

  • Assess

    The assessment phase can be co-funded by MAP Assess, which supports the diagnosis and business case.

  • Mobilize and migrate

    Execution can be supported by MAP Mobilize, which co-funds planning and migration, with additional incentives depending on the project profile.

Talk about mainframe modernization

AI in modernization

We accelerate with AI without giving up control

Translating code is only part of the work: architecture, integration, compliance and resilience still require engineering and experience. That's why we use AI where it delivers the most value, speeding up the most labor-intensive steps, always with human validation and traceability.

AWS Transform for Mainframe

We apply AWS Transform for Mainframe, AWS's agentic AI service built specifically for mainframe modernization. Its agents analyze COBOL, CICS, DB2 and VSAM codebases in hours or days, generate documentation and a map of business rules, and support three modernization paths.

  • Refactor

    Automated conversion from COBOL to functionally equivalent Java, with a code-quality uplift.

  • Replatform

    COBOL recompiled to run on AWS, preserving functional equivalence.

  • Reimagine

    Extracting business rules to redesign the application into modern architectures, such as microservices.

Across all paths, our specialists validate business rules, architecture boundaries and requirements. The result is a timeline of months instead of years, without giving up control.

AWS Transform and Kiro act as supervised refactoring engines, already responsible for these numbers in previous initiatives.

  • 65%

    reduction in project time

  • 90%

    automated test coverage

Modernization that delivers real results

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Partner ecosystem

Complex solutions start with one simple step

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