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AI-powered legacy code conversion to readable Java, ensuring functional equivalence and long-term maintainability.
Bloop AI is a cutting-edge research lab and startup specializing in AI-powered legacy code conversion. Based in New York and backed by prominent investors including Y-Combinator, Bloop AI is dedicated to solving the long-term challenge of legacy code modernization. Their primary focus is on converting COBOL to Java, producing code that is not only functionally equivalent but also highly readable and maintainable, effectively eliminating the issues associated with traditional conversion methods like "Jobol" or "Cava."
Traditional code conversion often results in unreadable and unmaintainable code. Bloop AI pioneers a new approach using advanced AI, combining Large Language Models (LLMs) with compiler-based accuracy. This innovative method generates Java code that reads as if a human wrote it, making it ready for immediate integration and further development within an organization's core engineering systems.
Bloop AI aims to free engineering resources from the burden of legacy code, enabling businesses to innovate faster and stay competitive.## What is Bloop AI? Bloop AI is a startup research lab focused on AI and programming languages, dedicated to solving the complex challenge of legacy code modernization. They specialize in converting legacy code, primarily COBOL, into modern, readable, and maintainable Java. Backed by leading investors and Y-Combinator, Bloop AI leverages advanced AI, including LLMs and compiler accuracy, to ensure functional equivalence and high-quality output.
Bloop AI follows a structured modernization process:
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Converts legacy COBOL code into human-readable Java, ensuring maintainability and reducing the need for extensive refactoring.
Utilizes AI and compiler accuracy to ensure that the converted Java programs function identically to the original COBOL programs, validated by an AI test suite.
Modernized code incorporates open-source libraries and cloud primitives, leading to significant cost savings on licensing and infrastructure.
Automated translation process includes built-in correctness checks, making it a safer and more reliable alternative to manual code rewrites.
The process includes an initial survey, a proof-of-concept, and full modernization, ensuring a smooth transition and immediate innovation capabilities for the client's team.