Modernize legacy systems 4x faster with AI-driven code translation, automated refactoring, and intelligent migration strategies. Transform COBOL, mainframe, and monolithic applications to modern cloud-native architectures.
AI-powered legacy modernization uses advanced machine learning to automatically analyze, translate, and refactor legacy code into modern languages and architectures. It reduces modernization time from years to months while preserving business logic and improving code quality.
Intelligent automation from code analysis to production deployment
AI translates COBOL, PL/I, RPG, and other legacy languages to modern Java, C#, Python, or Go. Preserves business logic with 99.9% accuracy while generating idiomatic, maintainable code.
Goes beyond translation to modernize code structure. AI identifies anti-patterns, applies SOLID principles, and refactors monolithic code into maintainable, testable modules.
Automatically migrates from DB2, IMS, VSAM to modern databases. AI generates schema translations, data migration scripts, and ORM mappings while preserving referential integrity.
AI automatically wraps legacy business logic in modern REST/GraphQL APIs and generates integration code for cloud services, enabling gradual strangler-fig migration patterns.
AI generates comprehensive unit, integration, and regression tests by analyzing legacy code behavior. Achieves 85%+ code coverage automatically, ensuring migration accuracy.
AI analyzes dependencies and generates phased migration plans that minimize risk. Enables parallel running of legacy and modern systems during transition.
Global bank migrated 2.5M lines of COBOL to Java microservices in 18 months using AI translation. Achieved 70% cost reduction in mainframe spend while improving transaction speed by 10x.
Insurance provider modernized 30-year-old PL/I system to cloud-native architecture. AI-generated APIs enabled mobile integration while maintaining 99.9% business logic accuracy.
Telecom giant migrated RPG-based billing system (800K lines) to microservices in 12 months. AI refactoring improved code maintainability by 65% and reduced technical debt significantly.
State agency modernized 40-year-old benefits system using strangler-fig pattern. AI-generated APIs enabled gradual migration while maintaining service to 5M+ citizens without disruption.
Yes. CogniX.AI achieves 99.9% business logic preservation by training on millions of lines of COBOL code and using semantic analysis to understand business intent, not just syntax. We validate translations with automated regression testing.
AI modernization is 4-5x faster than manual rewrites. A typical 1M-line COBOL system takes 18-24 months with AI vs 5-7 years manually. AI also reduces risk by preserving existing business logic rather than reimplementing from scratch.
AI automatically migrates DB2, IMS, and VSAM databases to modern platforms (PostgreSQL, Oracle, SQL Server). We generate schema translations, data migration scripts, and validation tests. You can run parallel for validation before cutover.
Yes. CogniX.AI supports strangler-fig patterns where we wrap legacy components with APIs and gradually replace them. AI analyzes dependencies to create risk-minimized migration phases that enable parallel running.
AI excels at discovering undocumented logic by analyzing code behavior, data flows, and execution patterns. We generate comprehensive documentation and tests for the modernized code, making it maintainable for future developers.
Join enterprises saving 70% on modernization costs with AI-powered code translation