AI-Accelerated Modernization 

At 2Oaks, we use AI engineering tools to make previously uneconomical modernization projects viable. Our service compresses timelines, reduces costs, and de-risks the upgrade, migration, and containerization work that traditional approaches struggle to justify on a business case. Legacy estates of twenty to fifty applications that would conventionally take two to three years can be addressed in a fraction of that time, freeing budget for the parts of the program that genuinely need human attention. 

Key Components of Our Service

  • The longer aging runtimes are deferred, the greater the compounding risk grows. Our team will: 

    • Upgrade legacy frameworks and runtimes to modern, supported versions 

    • Update project files, configuration, and deprecated APIs with validation through your existing pipelines 

    • Preserve your organization's coding standards through reusable remediation patterns 

  • dernization is also the moment to pay down years of accumulated risk. We help: 

    • Identify and remediate architectural anti-patterns, dead code, and outdated dependencies 

    • Resolve security vulnerabilities surfaced during upgrade, including transitive dependencies 

    • Generate or update tests to lock in behaviour before and after each transformation 

  • Real return comes from replatforming, not lifting-and-shifting. Our experts will: 

    • Swap legacy and on-premises dependencies for modern cloud-native services 

    • Validate functional equivalence and performance after each change 

    • Identify opportunities to introduce AI capabilities during modernization 

  • Code transformation is complete only when it is running safely in production. We help: 

    • Generate Dockerfiles, infrastructure-as-code, and CI/CD pipelines for cloud deployment 

    • Provide architect-led oversight on every meaningful change 

    • Establish telemetry and cost monitoring to validate the business case 

Partner with 2Oaks to turn cost-prohibitive modernization challenges into achievable, funded initiatives, unlocking the agility, security, and AI-readiness your organization needs. 

Insights from our 2Oaks Team

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AI-Accelerated Modernization Technical Brief

  • The longer aging runtimes are deferred, the greater the compounding risk grows. Our team will: 

    • Upgrade .NET Framework applications to modern .NET (8, 9, or later) and Java applications to JDK 21 with Spring Boot 3.x using GitHub Copilot App Modernization's predefined scenarios and OpenRewrite transformations 

    • Update project files, configuration, and deprecated APIs automatically, with every change validated through existing build and test pipelines 

    • Preserve your organization's coding standards and architectural conventions by encoding them as custom skills, reusable remediation patterns that improve as more applications pass through the pipeline 

  • Modernization is also the moment to pay down years of accumulated risk. We help: 

    • Identify and remediate architectural anti-patterns, dead code, and outdated dependencies flagged during AI analysis 

    • Automatically resolve Common Vulnerabilities and Exposures (CVEs) surfaced during the upgrade process, including transitive dependency vulnerabilities 

    • Generate or update unit and integration tests using GitHub Copilot to lock in behaviour before and after each transformation, so refactoring does not silently change system behaviour 

  • Lifting-and-shifting delivers little value on its own. The real return comes from replatforming onto Azure-native services. Our experts will: 

    • Apply GitHub Copilot App Modernization's predefined migration tasks to swap on-premises and legacy dependencies for Azure equivalents: Windows Active Directory to Microsoft Entra ID, plaintext credentials to Managed Identity and Azure Key Vault, MSMQ or RabbitMQ to Azure Service Bus, local Redis to Azure Cache for Redis, SMTP to Azure Communication Services, local logging to OpenTelemetry, and Amazon S3 to Azure Blob Storage 

    • Validate functional equivalence and performance after each migration task, with full transparency into every change 

    • Identify opportunities to introduce AI capabilities during modernization, such as grounding a legacy app's search with Azure AI Search, embedding Microsoft Foundry agents for user assistance, or exposing capabilities through Model Context Protocol (MCP) servers so they can be consumed by Microsoft 365 Copilot and other agents 

  • Code transformation is only complete when it is running safely in production. We help: 

    • Generate Dockerfiles, Bicep infrastructure-as-code, and CI/CD pipelines for deployment to Azure App Service, Azure Container Apps, Azure Kubernetes Service (AKS), or AKS Automatic 

    • Provide architect-led oversight throughout the modernization process, reviewing agent output, catching regressions, applying organizational standards, and keeping humans firmly in the loop on every meaningful change 

    • Establish the telemetry, observability, and cost-monitoring practices needed to run the modernized application confidently on day one, and to validate that the investment is delivering the business case that justified it 

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