AI-Powered Application Engineering and Modernization ––
Build New Applications. Modernize What Already Works.
InfoMagnus designs, builds, and modernizes applications across web, mobile, desktop, and cloud environments.
We combine experienced engineers, AI-assisted workflows, automated testing, and GitHub-native delivery to move software from idea to production with greater speed and control.
We combine experienced engineers, AI-assisted workflows, automated testing, and GitHub-native delivery to move software from idea to production with greater speed and control.
AI-powered app Modernization Services —
Choose the Right Path for Every Application.
Not every application needs the same answer. InfoMagnus helps teams determine what to retain, extend, modernize, replace, or build from the ground up, then turns that strategy into working software.
Determine whether to build, retain, extend, replace, or modernize. We assess business goals, architecture, dependencies, code quality, security, and system behavior, then create the documentation and delivery plan needed to move forward.
Apply InfoMagnus’ SONYX framework to analyze, document, test, stabilize, refactor, and validate legacy applications. Its structured phases and AI-assisted workflows help teams modernize in controlled increments while preserving critical business behavior.
Design and build new applications for web, cloud, iOS, Android, Windows, and macOS. We move from requirements through architecture, development, testing, and release using AI-assisted engineering and GitHub-native delivery.
Modernize applications built on mainframes, unsupported languages, and aging frameworks. We map critical business logic, reduce dependency risk, and move workloads toward maintainable architectures without forcing a high-risk rewrite.
Update application architecture, APIs, frameworks, databases, cloud infrastructure, containers, integrations, and runtime environments. We improve how applications scale, connect, deploy, and operate while reducing technical debt.
Build behavioral baselines and automated test coverage before major changes begin. We compare each modernized release with existing system behavior to catch regressions and protect critical business functions.
Build GitHub Copilot, GitHub Actions, automated testing, security scanning, quality gates, environments, and deployment controls into the delivery system. Teams gain repeatable workflows and clear controls from development through release.
Building Value ––
Modernization Needs More Than AI.
AI can accelerate modernization, but it cannot replace the system around it. InfoMagnus brings the structure, testing, documentation, governance, and engineering expertise needed to modernize legacy applications with speed and control.
AI can generate code, but it needs clear goals, defined tasks, and expert review. InfoMagnus gives modernization work the structure needed to produce usable, reliable results.
Modernization cannot put the business at risk. We strengthen testing, documentation, and validation so teams can improve legacy systems without breaking what already works.
Fast delivery only matters when quality holds. InfoMagnus combines AI-assisted engineering, SONYX, and GitHub-native workflows to help teams move faster while keeping governance, security, and delivery discipline intact.
AI-Powered App Modernization —
How We Cut Application Modernization Time by 55% Using GitHub Copilot.
Innovation In action ––
We Built A Modernization System Around AI with SONYX.
A multi-agent modernization platform designed to accelerate product engineering and SDLC execution inside GitHub-native workflows. SONYX breaks modernization into structured, consumable tasks that specialized AI agents can execute with greater consistency, governance, and operational control.
Built Around GitHub: The 7-Phase InfoMagnus Modernization Framework.
We don't start with code generation. We start with understanding.
Every phase in the framework exists because skipping it creates downstream rework, and we've seen what happens when teams skip phases.
Every phase in the framework exists because skipping it creates downstream rework, and we've seen what happens when teams skip phases.
Establish a behavioral baseline before modernization begins.
We build test coverage against current system behavior, targeting at least 70% coverage to reduce regression risk.
We build test coverage against current system behavior, targeting at least 70% coverage to reduce regression risk.
Address only critical vulnerabilities and operational bugs before modernization begins.
For TBS-TimeWarp, InfoMagnus prioritized 70 CVEs, including 23 critical and 47 high-risk issues.
For TBS-TimeWarp, InfoMagnus prioritized 70 CVEs, including 23 critical and 47 high-risk issues.
Translate the architecture understanding into a tactical migration roadmap.
Define success criteria per phase, identify risk controls, and break large work into focused, measurable chunks.
Define success criteria per phase, identify risk controls, and break large work into focused, measurable chunks.
Build the foundation for incremental migration using the Strangler Fig pattern, with adapters and facades that let old and new systems coexist while features move gradually.
Implement CI/CD pipelines, automated testing at every commit, and incremental deployments.
Automated quality gates mean verification is built into the process, not bolted on at the end.
Automated quality gates mean verification is built into the process, not bolted on at the end.
Documentation is not a deliverable you produce at the end of a project. It's a living artifact you maintain throughout.
This phase establishes the continuous improvement loop that keeps the modernized system from accumulating new debt.
This phase establishes the continuous improvement loop that keeps the modernized system from accumulating new debt.
Explore More About SONYX.
Modernize Applications Without Losing Control.
Explore how InfoMagnus helps enterprises modernize critical applications with AI-assisted delivery and GitHub-native engineering.
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