AI-Assisted Legacy Modernization

Define boundaries. Unlock modular modernization.

Monolithic legacy systems resist change by design, with intertwined dependencies, ambiguous business domains, and hidden side effects that make every release risky. Our scoped decomposition strategy breaks these patterns, enabling incremental modernization with zero disruption to ongoing delivery.

• Modular boundary mapping. We apply advanced code and architecture analysis, supported by hyper-specific prompting for AI agents, to segment legacy monoliths by business domain, integration contract, and database dependency. Each module is evaluated for functional cohesion, change risk, and decoupling feasibility.
• Slice definition & isolation. Using the AI Solution Accelerator™ approach, we define precise migration slices by business value, API surface, and testing scope. Every slice is scoped for independent development and deployment, with clear rollback boundaries and integration touchpoints. This approach avoids “big bang” cutovers, turning monolith extraction into a controlled, iterative process.
• Delivery decomposition guides. We deliver actionable decomposition playbooks that detail migration criteria, integration rules, and QA requirements for every modernization slice. Rollback and test isolation steps are predefined, allowing releases to move forward without the need for complete rearchitecture. Each playbook covers stakeholder maps, dependency blockers, and handover instructions — keeping engineers, QA, and business owners fully aligned on modernization goals at every stage.
• Parallel execution. Scoped decomposition is designed for real-world delivery. Modernized slices are delivered in parallel with existing feature releases, using side-by-side execution and progressive rollout. We track dependency shifts, regression risks, and test coverage deltas at every step, keeping business-as-usual releases stable.
• AI-driven decision support. Agent assist AI supports decomposition with real-time dependency maps, risk heatmaps, and slice impact forecasting.

Scoped decomposition turns monolithic inertia into controlled, modular progress.

With Devox and the AI Solution Accelerator™, legacy modernization becomes an engineering discipline.

Reveal what legacy systems conceal. Plan with precision.

Legacy migrations stall when complexity goes unseen. Our AI-powered assessment framework — guided by the AI Solution Accelerator™ approach — maps your entire codebase, identifies architectural debt, and generates a phased roadmap built for real-world execution. Planning is led by AI-powered analysis, with human engineers prompting, steering, and validating every transformation.

• Semantic mapping of architecture. Our engineers apply AI Solution Accelerator™ practices to extract code-level semantics, undocumented logic, and hidden integrations across legacy systems. Parallel audit, testing, and governance tracks ensure that the mapping is both technically exhaustive and policy-aligned, giving full visibility into the operational anatomy of your platform — down to every module, slice, and dependency.
• Technical debt indexing. Using static analysis tools integrated into our modernization pipeline, we build a detailed profile of your codebase: complexity, coupling, churn, and risk exposure. Every insight feeds into a technical heatmap, enabling AI-assisted diagnosis of architectural debt and supporting faster, cleaner modernization slicing.
• Business logic discovery. We trace critical flows, like billing engines or compliance validators, through tangled code layers. Legacy logic is deconstructed, documented, and cross-mapped against business priorities. This forms the basis of slice-by-slice continuity assurance during modernization, aligned with the best practices for AI-assisted modernization that preserve business logic at every step.
• Phased roadmap with prioritized slices. The result is a modernization plan grounded in technical depth and business logic. Each modernization slice is bounded, prioritized, and mapped to delivery effort and risk.
• Delivery enablement. Everything extracted — code issues, logic traces, delivery checkpoints — translates directly into the engineering backlog. Acceptance criteria, edge cases, and testing scope are embedded. Our AI Solution Accelerator™ approach ensures your roadmap is delivery-ready from day one.

This is how Devox accelerates legacy modernization — with a structured approach that makes every decision traceable, every risk visible, and every delivery slice grounded in data. Modernization stories, dependencies, and slice boundaries are mapped directly into your Nx monorepo and issue tracker, giving your team instant, actionable backlog.

Move with confidence. Architect for what’s next.

Legacy systems limit scale and uptime. We transition workloads to cloud-native infrastructure through modular replatforming, automated pipelines, and hybrid-ready architecture. Each slice is delivered under the AI Solution Accelerator™ with iterative simplicity, supported by a DevOps stack that includes Nx monorepos, Terraform, containerization, and observability tools. This ensures every step is reproducible, secure, and aligned with enterprise governance, without disrupting ongoing delivery.

• Cloud-ready architecture planning. We assess your infrastructure, service dependencies, and runtime profiles to define the optimal cloud migration strategy: lift-and-shift, replatforming, or full reengineering. Each path is phased for zero disruption, with domain-specific risk analysis.
• Infrastructure automation & IaC implementation. We codify infrastructure using Terraform or Bicep, enabling version-controlled, reproducible environments. IaC patterns are integrated into slice deployment pipelines, governed by CI/CD quality gates and cloud security policies.
• Containerization & service isolation. Legacy applications are decoupled and containerized using Docker, Kubernetes, or Azure App Service — a process that starts with understanding how to refactor COBOL/Java/.NET with AI while preserving critical behavior.
• Hybrid deployment models. We support hybrid integration scenarios, including legacy on-premises systems integrated with cloud workloads, as well as multi-cloud environments spanning Azure, AWS, and GCP. Cloud interoperability layers are built using message buses such as Azure Service Bus or Kafka, API gateways, and secure secrets management with tools like Vault and Key Vault.
• CI/CD-Aware migration readiness. Before migration begins, we assess the maturity of your existing CI/CD pipelines: coverage, automation level, and alignment with the best practices for AI-assisted modernization to ensure smooth execution. If gaps are found, we bootstrap or extend pipelines to ensure each modernization slice can move through delivery gates with full automation and rollback capability..
• CI/CD-enabled cloud delivery pipelines.  Each migrated slice is deployed via CI/CD pipelines (GitHub Actions, Azure DevOps), with integrated test automation (Playwright, Postman, SonarQube). Our AI Solution Accelerator™ embeds observability, rollback logic, and policy checks in every stage.

Devox engineers don’t just migrate workloads — they reconstruct your foundation for automation-first delivery, where the AI vs manual modernization cost comparison validates long-term scalability and savings. Through our AI Solution Accelerator™ framework, cloud transformation evolves into an ongoing process, embedded across strategy, execution, and operations. It’s an operational layer from the first delivery slice.

Restructure with precision.

Legacy systems grow dense over time, with entangled logic, outdated patterns, and invisible coupling. We refactor them into modular, maintainable, and future-ready components, guided by AI-assisted Python programming techniques when applicable under our AI Solution Accelerator™ approach. Each modernization slice runs with parallel validation tracks, automated testing, audit checks, and governance guardrails, while DevOps pipelines enforce quality gates through SonarQube, Playwright, and GitHub checks.

• Modular decomposition. We segment legacy codebases into cleanly bounded modules based on business domains, integration contracts, and database boundaries. Each slice is scoped for independent refactoring, testing, and delivery, enabling phased modernization without system disruption.
• IDE-level AI refactoring agents.  Our engineers work inside IDEs enhanced for AI-assisted coding, enabling real-time pattern recognition, method extraction, logic simplification, and type transformation. Refactor sessions are traceable, reversible, and tied to quality gates.
• Dead code elimination.  Using static analyzers and usage telemetry, we eliminate unreachable code paths, remove legacy constructs (e.g., nested conditionals, static branches), and rebuild core flows with modern programming patterns that support maintainability and testability.
• Behavioral integrity. We preserve behavioral integrity by keeping application behavior intact through test-driven transformation.
• Cross-functional readiness mapping. Before we validate a modernization slice, we map non-functional requirements — performance targets, security constraints, observability needs, and fault tolerance — directly into the refactoring scope. These requirements are treated as first-class criteria, ensuring that modernized components align fully with code correctness, as well as operational and business SLAs.

AI-Powered Code Refactoring transforms tangled legacy into clean, modular foundations — lowering maintenance cost, improving developer velocity, and preparing your system for seamless future upgrades.

Expose legacy logic. Connect with everything.

Legacy applications often trap critical functionality behind outdated interfaces, monolithic architectures, or tight coupling. We enable structured API access to legacy systems, transforming hidden logic into scalable, connected services under the AI Solution Accelerator™. This includes modernizing integrations from SOAP to REST or GraphQL, enabling event-driven flows with Kafka, and wrapping core modules for side-by-side execution. The result is a service layer that unlocks innovation without breaking continuity.

• Legacy logic wrapping. We extract internal logic from legacy systems and expose it through structured REST or gRPC APIs. This allows teams to integrate without rewriting entire modules. Business-critical flows remain stable and version-controlled throughout the transition.
• API gateway integration. We connect legacy and modern services through secure, centralized gateways. API requests are routed, validated, and monitored with full observability. Service mesh patterns (when needed) are applied for distributed identity, retries, and circuit breaking.
• Data interoperability. We transform outdated SOAP/XML payloads, flat files, or custom protocols into JSON or Protobuf interfaces. Legacy inputs and outputs are normalized for compatibility with mobile apps, modern frontends, and partner systems.
• Side-by-side execution. Using event-based patterns and lightweight orchestration, we decouple legacy execution paths from new services. Legacy modules and API-enabled services can run side by side, enabling incremental cutovers with behavioral guarantees.
• AI-orchestrated contract generation. As part of our AI Solution Accelerator™, contract schemas (OpenAPI, Protobuf) and test suites are generated automatically from observed legacy behavior. This accelerates documentation, validation, and CI integration for each exposed interface.

API enablement functions as a transformation layer rather than a superficial wrapper. Devox applies the AI Solution Accelerator™ to elevate legacy logic into maintainable, testable, and extensible APIs, all while preserving business continuity.

Upgrade the experience. Streamline every interaction.

Legacy frontends limit user efficiency and product evolution. We modernize outdated interfaces into fast, modular, and accessible Single-Page Applications, delivered through AI-augmented workflows within our AI Solution Accelerator™ framework. Using frameworks like Angular, React, or Blazor, we decouple presentation from business logic and enforce governance guardrails for accessibility, performance, and compliance. The result is a modern experience layer engineered for scale, usability, and continuous evolution.

• Architecture redesign. We decouple legacy UI logic from server-side rendering engines (e.g., Razor, JSP, Smarty) and rebuild with modern SPA frameworks like React or Angular. Presentation logic is cleanly separated from business logic and API access, enabling long-term flexibility.
• AI-assisted component extraction. Our AI Solution Accelerator™ includes agents that scan server-rendered templates to identify reusable UI components, patterns, and layout structures. These are restructured into maintainable frontend modules, accelerating the transition to modern view layers.
• Accessibility & performance upgrades. We audit the modernized UI against WCAG, ADA, and performance benchmarks. Components are refactored for keyboard navigation, screen reader compatibility, lazy loading, and responsive design, ensuring broad usability with enterprise-grade speed.
• Progressive web app (PWA) Enablement. Where appropriate, we extend SPA frontends into PWAs, adding offline capabilities, push notifications, and mobile-native UX without duplicating logic. This allows legacy business platforms to reach mobile use cases without separate native apps.
• Design system integration. We define or integrate scalable design systems (e.g., Tailwind, Material, custom UI kits) to bring consistency across the new interface. The Accelerator governs UI consistency with auto-generated snapshots, screenshot testing, and theme validators.

With the AI Solution Accelerator™, Devox modernizes UI at the code, structure, and experience level, without breaking what still works.

Build confidence into every release.

Legacy systems rarely come with reliable test coverage, reproducible builds, or scalable pipelines. We embed automated quality controls and delivery pipelines as part of every modernization stream, using our AI Solution Accelerator™ to validate each refactored slice, reduce risk, and streamline deployment. Continuous validation and governance are embedded in every slice, with audit tracks running in parallel to modernization and delivery.

• Slice-based test scaffolding. Each modernization unit is accompanied by auto-generated unit and integration tests. AI agents analyze function signatures, control flow, and data access patterns to scaffold tests with appropriate mocks and assertions, ensuring confidence at the slice level.
• Intelligent CI/CD Pipelines. We modernize and modularize your CI/CD pipelines to support parallelized testing, canary deployments, rollback logic, and real-time observability. Our team sets up delivery gates with automated linting, type checks, test coverage thresholds, and static analysis integrated into each commit cycle.
• Legacy-to-modern pipeline bridging. During the transition, we maintain dual-mode support where legacy delivery workflows (e.g., FTP uploads, monolithic scripts) coexist with modernized GitOps pipelines. This ensures zero disruption while de-risking the cutover phase.
• Environmental parity. We use containerized environments and ephemeral test deployments to validate behavior across staging and production-like conditions. All changes are tested in realistic contexts before promotion, preventing late-stage surprises.
• AI-enhanced observability setup. We upgrade observability infrastructure to ensure that all telemetry from the modernized system, including CI/CD signals, production metrics, and structured logs, is captured and visualized. Using Prometheus, Grafana, and OpenTelemetry, we build real-time dashboards that give DevOps full visibility into system behavior, deployment health, and performance deviations.

CI/CD Modernization turns every release into a controlled business event, cutting deployment risk, shortening release cycles, and giving you full confidence that modernization delivers measurable value without disruption.

Stabilize change. Shrink regression risk.

Legacy migrations fail when code is modernized faster than it’s tested. We embed testing directly into the modernization process, from the first line of refactored code to production rollout, using a layered, AI-augmented strategy.

• Automated slice-level testing. Each refactored slice is independently testable. We embed test scaffolding at the boundary of every module, with the AI Solution Accelerator™ generating initial test scenarios based on code behavior, expected side effects, and historical bug patterns.
• AI-guided risk mapping. We apply AI-assisted heuristics to identify high-risk zones in legacy code — dead branches, false positives, flaky logic — and flag them early in the refactor cycle. This lets teams focus testing effort where it matters most.
• Regression-proof pipelines. Testing is wired into the CI pipeline from day one. We maintain green builds through test coverage diffs, behavioral validation, mutation testing, and pipeline-integrated checkpoints, so every modernization step is verifiable and shippable.
• Legacy behavior benchmarking. Before each cutover, we compare the new behavior to the legacy system using both synthetic tests and live capture replays. Differences are inspected jointly by AI and human reviewers to ensure no core business logic drifts undetected.
• Per-slice quality gates. Each modernization slice passes through its own quality gates — code checks, test coverage, and release validation are all tracked slice-by-slice, with metrics and reporting built in.

Modernization goes beyond a simple rewrite — it’s a controlled evolution. With the AI Solution Accelerator™, testing stays ahead of development. It leads the way.

Validate what’s been modernized.

Successful modernization ends with confidence — in the codebase, in the handoff, and in the team’s ability to evolve what’s next. Your team inherits a system that’s both rebuilt and deeply understood. We ensure this through deep post-refactor reviews and structured technical narratives.

• Slice-by-Slice Audits. Each migration slice undergoes behavioral, structural, and operational review. We confirm architectural alignment, interface stability, and runtime behavior under load. AI agents flag anomalies across performance, dependency bloat, or misaligned side effects.
• Architecture Narratives. We document the why behind the change, focusing on what was altered, which patterns were replaced, which risks were mitigated, and which business logic was preserved. This forms a clear, high-fidelity artifact that enables safe onboarding, support, and future change.
• Operational Playbooks. We deliver hands-on documentation for every critical flow — including integration points, rollback paths, deployment constraints, and observability hooks. These are written and validated as if your team had built the system themselves.
• Collaborative Handover. Our engineers join your team for shadow cycles, knowledge walkthroughs, and backlog grooming. This structured handoff eliminates post-migration drift, ensuring that modernization becomes part of your SDLC.

With the AI Solution Accelerator™, ownership is transferred through deep understanding, supported by well-structured, transparent code.