Kaizen
Autonomous Software Modernization and Quality Engineering for Legacy Systems.
Automated technical debt remediation and legacy modernization for enterprise scale.
Codefix represents a pivotal shift in the 2026 software engineering landscape, moving beyond simple code generation into the more complex territory of automated architectural remediation. Built on a proprietary semantic code graph and fine-tuned Large Language Models (LLMs), Codefix specializes in identifying and automatically fixing technical debt, security vulnerabilities, and deprecated dependencies across massive codebases. Unlike standard linters, Codefix understands the functional context of code, allowing it to perform high-fidelity migrations—such as upgrading Java 8 monoliths to Spring Boot 3 microservices or refactoring COBOL logic into modern C#. Its architecture is designed for the Enterprise, featuring a deterministic engine that ensures code changes remain functionally equivalent to the original source while adhering to modern clean code standards. By 2026, Codefix has positioned itself as the 'Auto-Pilot for Maintenance,' significantly reducing the 40% of developer time typically lost to technical debt. The platform integrates directly into CI/CD pipelines, acting as a proactive gatekeeper that not only identifies issues but submits ready-to-merge Pull Requests with comprehensive unit tests to validate the fixes.
Uses a multidimensional graph to map code dependencies and logic flow rather than simple text patterns.
Autonomous Software Modernization and Quality Engineering for Legacy Systems.
Bridge the gap between natural language and complex database architecture with AI-driven query synthesis.
Add AI-powered chat and semantic search to your documentation in minutes.
Automated Technical Documentation and AI-Powered SDK Generation from Source Code
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Automatically generates JUnit or PyTest suites for every refactored code block to ensure functional parity.
Determines if a vulnerable library is actually reachable via the execution path.
Neural-symbolic translation from legacy formats (COBOL/Mainframe) to Java/C#.
Allows teams to write custom Rego or YAML rules that trigger automated refactoring.
Identifies and removes unused methods, classes, and dependencies across microservices.
Breaks down massive upgrades into small, testable PRs over time.
A zero-day exploit in a common library affects 400 microservices simultaneously.
Registry Updated:2/7/2026
Legacy monolithic application needs to be containerized and move to Kubernetes.
Technical debt from 10-year-old Java versions preventing the use of modern performance features.