Legacy Code Modernization
Deploy localized, air-gapped AI coding models to autonomously translate proprietary legacy codebases (e.g., COBOL) into modern stacks without exposing source code to public clouds.
The Baseline
Translating proprietary, 30-year-old COBOL codebases to modern stacks is risky, manual, and prohibitively expensive. Uploading the source code to public LLMs (like OpenAI or GitHub Copilot) is a massive security violation that risks exposing core enterprise intellectual property and financial algorithms.
Local, air-gapped coding models are deployed inside the corporate VPC to securely analyze the monolithic architecture and translate it line-by-line into modern languages (e.g., Java or Go).
Modernizes technical debt securely without leaking core intellectual property. Engineering teams accelerate legacy migration by 10x while maintaining absolute data sovereignty over their foundational source code.
Architecture Flow
Secure Repository Ingestion
Engineering teams clone the legacy COBOL repository directly into a secure, isolated AVELIN storage layer hosted entirely on-premise or within a heavily fortified VPC.
Contextual Analysis (Y-Ray Data)
The Y-Ray Data engine parses the monolithic codebase. It maps complex internal dependencies, legacy business logic, and decades of undocumented variable structures to create a searchable, semantic blueprint of the software.
Air-Gapped Translation (Model Engine)
The Model Engine allocates local GPU compute to process the codebase chunk-by-chunk using a specialized open-source coding model (e.g., Code Llama). The model translates the legacy syntax into modern, object-oriented microservices.
Automated Documentation & Verification
As the model rewrites the logic, it generates comprehensive inline documentation. y-ray deep-trace maps every new line of modern code directly back to the original COBOL logic block, ensuring auditors and QA teams can verify mathematical and functional equivalency.
Core Infrastructure
| Component | Role |
|---|---|
| Model Engine | Manages the localized deployment of high-parameter coding models on internal hardware, enabling complex architectural translation without requiring internet access. |
| Y-Ray Data | Indexes the entire legacy codebase, providing the AI with deep contextual grounding to ensure it doesn't hallucinate modern syntax that breaks historical business rules. |
| y-ray Deep-Trace | Generates a line-by-line translation map, providing an immutable audit trail that proves the modernized microservice perfectly mirrors the legacy mainframe's logic. |
Technical Specifications
AES-256 for data at rest; TLS 1.3 for internal network transit
PCI-DSS (for financial core banking translation), SOC2, and strict corporate IP protection frameworks
Deploys natively on physically isolated bare-metal servers or highly secure, closed-loop AWS/Azure VPCs
Build this architecture
Map this workflow to your internal data models. Deploy AVELIN AI to gain sovereign control over your enterprise intelligence.
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