Metabob

Metabob is an AI-powered software analysis tool designed to review and refactor legacy code to reduce overall code complexity. It uses Graph Neural Networks (GNNs) to analyze an entire codebase, understand data flow and architecture, and identify potential bugs, enabling automated or guided refactors. The system supports real-time review of new code, integration into IDEs and CI/CD pipelines, and on-premise deployment with use-case customization to fit organizational needs.

How Metabob Works

• Analyzes the complete codebase rather than isolated files to understand context, structure, and data flow.
• Uses GNN-based analysis to detect complex issues and determine the impact of problems on the entire project.
• Enables debugging and refactoring of legacy code, plus review of newly written code for early bug detection.
• Integrates into developers' IDEs and CI/CD pipelines to automatically perform AI code reviews on new code and provide feedback.
• Validates AI-generated code for correctness and cohesion with the existing codebase, suggesting improvements.

Use Case Customization

• On-premise deployment allows tuning to an organization’s specific needs.
• Users can define which detection categories matter most and tailor the system to leverage internal commit histories and bug fixes.

Competitive Advantage

• Combines LLM-based tooling with rules-based checks for robust coverage.
• Handles complex, context-rich codebases with strong retention of contextual information.
• High detection accuracy for compile-time and runtime issues, with adaptable problem descriptions and resolutions.

Customer Value

• Reduces debugging time and speeds up maintenance of large, messy codebases.
• Improves code quality and developer productivity by surfacing actionable insights.
• Provides a feedback loop to improve AI code generation over time by validating AI outputs within the real project context.

Get Started

• Integrates into your existing development workflow and CI/CD processes.
• Contact Metabob for a demonstration and to discuss on-premise deployment options.

Core Features

• End-to-end codebase analysis with Graph Neural Networks
• Real-time review of new code in IDEs and CI/CD pipelines
• AI-assisted debugging and refactoring of legacy systems
• Validation of AI-generated code for project cohesion
• On-premise deployment with use-case customization
• Detects compile-time and run-time issues with high accuracy
• Context-aware problem descriptions and remediation suggestions
• Support for large, complex codebases with strong contextual retention