Agentic Codecraft: Transforming Systems from Within

Our Agentic Code Transformation offering provides a cutting-edge solution for modernizing legacy Java and .NET applications to their latest stable versions (Java 17+, .NET 6/7/8). We achieve this through our advanced Agentic AI capabilities and powerful synergy of AWS-native tools.

At the core of our approach lies the strategic leverage of Agentic AI constructs, specifically through Amazon Q Developer. This empowers us to perform intelligent code analysis, generate highly accurate refactoring suggestions and autonomously create comprehensive unit tests. The result is a dramatic reduction in modernization timeframes, coupled with a significant enhancement in overall code quality.

Once your legacy applications are transformed using our Agentic AI solution, they are seamlessly integrated with Continuous Integration/Continuous Delivery (CI/CD) pipelines. This crucial step ensures automated and accelerated deployment cycles, drastically reducing the time to get new features and updates to your users.

Furthermore, these modernized applications are rigorously optimized for containerized deployment like ECS, EKS. This optimization not only enhances portability and resource efficiency but also unlocks the full potential of cloud-native scalability and resilience for your newly modernized applications.

Our comprehensive modernization process follows a structured and efficient methodology:

• Delivery Mechanism: Our Agentic Code Transformation solution is delivered through a meticulously orchestrated process that combines the power of AWS-native services with our proprietary Agentic AI frameworks.

1. Cloud-Native Platform as the Foundation: The core of our delivery leverages a robust, secure and scalable cloud platform, primarily AWS. This provides the foundational infrastructure for our Agentic AI agents to operate efficiently.

2. Modular Agent Deployment: We deploy a series of specialized AI agents, each with a distinct role in the modernization lifecycle (e.g. Code Analysis Agents, Refactoring Agents, Test Generation Agents, CI/CD Integration Agents). These agents are designed to work collaboratively, exchanging information and coordinating actions seamlessly.

3. Secure Data Ingestion and Processing: Legacy codebase and related metadata are securely ingested into the AWS environment. Our Agentic AI systems perform initial scans and analyses in isolated, secure processing environments.

4. Iterative and Automated Transformation: The transformation process is iterative. AI agents perform analysis, propose changes, execute refactorings and generate tests.

5. CI/CD Pipeline Integration by AI: A key aspect of our delivery is the automated integration of the transformed applications into your CI/CD pipelines. Our Agentic AI directly configures and optimizes these pipelines for containerized deployment on your chosen AWS target (ECS, EC2 Linux or EKS).

• Identify and Mitigate Risks: During the Discovery phase, we use AWS Transform for .NET and Amazon Q Developer for Java, .NET to assess compatibility, identify legacy API dependencies and automate unit test generation. We validate changes through side-by-side testing and Git-based version control for rollback. Windows dependencies are replaced with cross-platform solutions like Kestrel, environment variables or platform-agnostic logging. Code coverage is tracked and components below 70% are flagged for attention. Our Risk Identification and Mitigation Process aligned with the AWS Well-Architected Framework identifies and addresses risks early, with a formal Risk Register reviewed periodically.

• Secure AWS Account Governance: Our Security Standard Operating Procedures (SOPs) include a well-defined, repeatable process for governing AWS accounts, whether we manage customer-owned environments or provision accounts on their behalf. These practices are aligned with the AWS Startup Security Baseline and the AWS Well-Architected Framework - Security Pillar, ensuring robust security governance and compliance.

• Security Controls: For long-running workloads (e.g. automation jobs), we require machine access to utilize IAM roles attached to EC2 instances or Lambda functions, avoiding the use of static credentials. In production environments, we enforce environmental isolation by leveraging AWS Organizations and resource-level tagging to segregate access based on organizational units (OUs) and teams. To ensure the principle of least privilege, IAM Access Analyzer is employed to analyze and generate permissions based on actual usage patterns, reducing security risks.

• Our offering is ideal for:

1. Enterprises running Java 6/7/8 or .NET Framework 3.5–4.x applications.
2. Organizations moving from Windows to Linux, on-prem to cloud or monolith to microservices.
3. Businesses undergoing significant architectural shifts seeking to optimize their infrastructure.
4. Cloud architects and engineering leaders looking to enable CI/CD and containerization.