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Technical debt slows down innovation. Praxys uses AI-agentic workflows to automatically analyze, clean, and restructure large, messy codebases. We don't just change languages; we modernize design patterns, decouple dependencies, and bring your architecture up to enterprise standards.
Why "working" code is often a liability
Adding new features takes exponentially longer because the codebase is difficult to understand.
Outdated libraries, hardcoded credentials, and poor patterns expose the application to breaches.
Top talent leaves when forced to work on unmaintainable, 'spaghetti' code without clear structure.
Inefficient algorithms and database queries slow down application response times.
Our AI agents understand the *intent* of your code, not just the syntax. We systematically apply structural changes—like extracting interfaces, breaking down massive classes, and updating deprecated APIs—safely and automatically at a massive scale.
Targeted modernization of existing platforms
Identify tight coupling to databases or external services and abstract them behind proper interfaces.
Automate the tedious work of moving between major framework versions, handling breaking changes automatically.
Bring the entire repository up to standard with massive, automated applications of enterprise linting rules and formatting guidelines.
Improving structure without breaking behavior
Configuring SonarQube and custom scripts to map the exact locations and severity of technical debt.
Ensuring adequate unit test coverage exists before making changes. Using AI to generate missing tests.
Defining the architectural patterns, naming conventions, and best practices the code should conform to.
Deploying AI agents to systematically apply refactorings across designated modules.
Adding strict CI/CD checks to ensure technical debt cannot be reintroduced in the future.
The tools we use to enforce clean code
Let our AI-assisted teams clean your repository so your developers can focus on building new features.