Legacy Language and Framework Translation

Migrate mission-critical financial and transactional systems off expensive, rigid mainframes. AI agents translate COBOL business logic into modern, scalable Java microservices, enabling cloud deployment and agile development.

• Key Benefit: Eliminates vendor lock-in and reduces infrastructure costs by up to 60%.
• Real Example: A regional bank automated the conversion of its core loan processing system, cutting the projected 3-year migration timeline to 11 months and freeing its team to build new digital services.

Rescue decades of business logic trapped in desktop applications built on unsupported frameworks like VB6. AI translation converts these applications to modern, supported C# .NET Core or .NET 6+, enabling web deployment and integration with modern APIs.

• Key Benefit: Unlocks stranded data and processes, allowing for mobile and web access.
• Real Example: A manufacturing firm translated its legacy inventory management desktop app, enabling real-time data access for field teams via a secure web portal, improving operational visibility.

Modernize client-server applications with proprietary UIs that hinder user experience and scalability. AI agents decompose PowerBuilder client logic, translating it into a modern React frontend with a Node.js backend, creating a cloud-ready, responsive web application.

• Key Benefit: Dramatically improves user satisfaction and enables remote workforce capabilities.
• Real Example: A public sector agency transformed its citizen-facing permit system, reducing application processing time by 30% and cutting help desk calls related to client installation issues by 90%.

Escape the high costs and scarcity of developers for niche fourth-generation languages (4GLs) like Progress, Informix, or Uniface. AI translation converts business rules and reports into standard Python and optimized SQL, future-proofing your data and logic.

• Key Benefit: Mitigates critical talent risk and opens the ecosystem to modern data science and analytics tools.
• Real Example: A logistics company translated its core routing and scheduling engine from a proprietary 4GL, enabling integration with real-time traffic APIs and machine learning models for dynamic optimization.

Address severe security vulnerabilities and performance bottlenecks in aging web platforms. AI agents translate Classic ASP (Active Server Pages) into secure, high-performance .NET Core Web APIs, providing a modern integration layer for new frontends and mobile apps.

• Key Benefit: Closes critical security gaps and improves application performance by orders of magnitude.
• Real Example: An e-commerce retailer translated its product catalog backend, reducing page load times from 5+ seconds to under 300ms and passing a PCI DSS compliance audit for the first time in years.

Breath new life into rich desktop applications by translating Delphi codebases. AI can target multiple modern pathways, converting UI logic to frameworks like Electron or Avalonia for cross-platform deployment, and business logic to C# for cloud services.

• Key Benefit: Preserves significant investment in complex application logic while enabling deployment on modern OSs and the web.
• Real Example: A healthcare software provider translated its patient management system, allowing clinics to access the application via a browser without sacrificing the rich functionality of the original desktop client.

This critical first step quantifies the opportunity and builds executive buy-in. We conduct an AI-powered analysis of your legacy portfolio to identify the highest-ROI candidates for translation, such as business-critical VB6 or PowerBuilder applications. The output is a prioritized roadmap and a contained pilot project with clear success metrics, like converting a single module to demonstrate feasibility and establish a baseline for cost and speed.

Execute the pilot to validate the AI's translation quality and business logic preservation. This phase focuses on a non-critical but representative application component.

• AI agents perform the initial code translation from legacy to modern languages (e.g., COBOL to Java).
• Human-in-the-loop review ensures business logic integrity and architectural alignment.
• Key deliverable: A validated ROI model based on reduced maintenance costs, developer productivity gains, and risk mitigation, providing the concrete justification needed for full budget approval.

Scale the proven methodology across the prioritized portfolio. This phase establishes an automated translation factory with integrated quality gates.

• Agentic workflows orchestrate the end-to-end process: code extraction, translation, automated testing, and deployment staging.
• Continuous integration pipelines are built to validate each increment against functional and non-functional requirements.
• The result is a predictable, accelerated modernization wave that lifts developer capacity by 30-50% as they shift from maintaining dead-end code to building new features on modern platforms.

Transition the modernized codebase and the AI-powered toolchain to your internal teams for long-term ownership. This ensures sustainable value.

• Knowledge transfer sessions equip your developers with the skills to maintain and extend the new systems.
• Establish governance for ongoing technical debt reduction, using AI to continuously scan for new modernization opportunities.
• The outcome is a future-proofed IT estate with a repeatable process for incremental modernization, turning technical debt from a liability into a managed asset.

A major bank faced $15M+ in annual maintenance for a suite of 300+ PowerBuilder client-server applications. Using this roadmap:

• Pilot: Translated 5 core account management modules to C#/.NET Core in 8 weeks.
• Validation: Achieved 95% functional parity with automated tests; projected 40% maintenance cost reduction.
• Production: Scaled to modernize 50 applications/year, unlocking $6M in annual OpEx savings.
• Competitive Edge: Enabled rapid deployment of new digital banking features on a modern cloud stack.

CIOs cite three primary fears: business logic loss, ballooning costs, and project stall. Our phased approach de-risks each:

• Logic Integrity: AI translation is paired with symbolic reasoning checks and human validation at each phase to ensure semantic accuracy.
• Cost Control: The pilot delivers a firm, data-backed TCO/ROI before full commitment. Automation drives down marginal cost per application.
• Velocity Sustainment: The 'translation factory' model prevents slowdowns, turning a multi-year nightmare into a predictable, quarterly delivery program.