COBOL Colleague
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About
COBOL Colleague is a specialized AI-driven platform designed to bridge the gap between complex legacy mainframe applications and the modern business need for transparency. At its core, the tool uses deterministic AI to analyze COBOL source code and extract the underlying business logic, creating a structured causal knowledge graph. Unlike generative AI models that might hallucinate, this logic-based approach ensures that the information provided is precise and grounded in the system of record. It essentially acts as a documentation engine and a navigation system for mainframe environments that have become opaque over decades of maintenance. The tool works by unraveling complex code structures, such as problematic "GoTo" statements, to reveal the actual flow of business functionality. It provides users with a searchable "GPS" for their codebase, allowing them to isolate specific features and view data transformations or constraints in real-time. Stakeholders can access natural language descriptions of business rules directly from the code, making it easier to understand how specific calculations or regulatory checks are implemented without needing to manually trace thousands of lines of legacy syntax. This solution is primarily built for large-scale enterprises in sectors like finance, insurance, and government that rely on mainframe systems. It serves multiple roles within these organizations: developers use it to reduce the complexity of making changes; testers use it to identify the business processes impacted by updates; and compliance officers use it to verify that regulatory logic is correctly applied. It is also a significant asset for modernization teams who need to understand data flows before migrating to new architectures or for onboarding new developers who need to learn a massive codebase quickly. What distinguishes COBOL Colleague from standard static analysis tools is its focus on "business functionality" rather than just syntax. By creating a bridge between the technical implementation and the business purpose, it allows non-technical stakeholders to participate in the conversation about the application's future. Its use of deterministic reasoning provides a level of reliability required for mission-critical mainframe applications, ensuring that the insights generated are accurate reflections of the code's actual behavior.
Pros & Cons
Uses deterministic AI to ensure precise and accurate reasoning without hallucinations.
Extracts business functionality directly from the source code as the system of record.
Simplifies complex legacy code by unraveling unstructured logic like GoTo statements.
Provides natural language descriptions of business rules for non-technical stakeholders.
Accelerates onboarding by allowing new hires to self-serve their understanding of the codebase.
Specifically limited to COBOL applications, which may not suit multi-language legacy environments.
Requires a demo request to access pricing and full platform details.
Use Cases
Mainframe developers can isolate specific business features within massive codebases to reduce manual code tracing time.
Compliance officers can verify regulatory logic by following data transformations and reading natural language descriptions of calculated fields.
Onboarding managers can provide new developers with visualized documentation to help them understand the system without constant supervision.
Testing teams can identify exactly which business processes are impacted by a code change to create a more targeted testing strategy.
Modernization leads can map out data flows and business rules to prioritize which modules to migrate first based on complexity.
Platform
Task
Features
• automated documentation generation
• feature isolation in code viewer
• data flow and transformation analysis
• natural language business rule descriptions
• goto statement unraveling
• searchable code navigation (gps)
• causal knowledge graph creation
• deterministic ai reasoning
FAQs
How does COBOL Colleague differ from generative AI?
It uses deterministic AI and logic-based reasoning to provide precise information about code functionality. This eliminates the risk of hallucinations often found in generative models, which is critical for maintaining legacy mainframe systems.
Can the tool help with modernization or migration projects?
Yes, it identifies business processes executed by legacy code and maps data flows and transformations. This allows modernization teams to prioritize initiatives based on business value and complexity while ensuring accurate integration.
Does it provide documentation for the existing codebase?
The platform automatically creates up-to-date documentation of business functionality derived directly from the source code. This ensures the documentation remains the system of record even as the code changes over time.
How does it help with complex code logic like GoTo statements?
The tool untangles decades of complex code by unraveling GoTo statements and other legacy structures. This reveals the actual business process flow, making it significantly easier for developers to understand and modify the application.
Who within an organization can benefit from using this tool?
Beyond developers, it is designed for testers planning business process testing, compliance officers verifying regulatory logic, and business analysts looking to discover business rules. It also assists managers in onboarding new hires more efficiently.
Pricing Plans
Custom
Unknown Price• Deterministic AI analysis
• Business functionality extraction
• Causal knowledge graph
• Automated documentation
• Searchable code navigation
• Natural language descriptions
• Modernization analysis
• Regulatory compliance tracing
Job Opportunities
There are currently no job postings for this AI tool.
Ratings & Reviews
No ratings available yet. Be the first to rate this tool!
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