Hypercubic AI: Modernizing the Legacy Systems Powering the Global Economy

The global economy runs on systems most people have never heard of. While Silicon Valley chases the next big thing in AI and blockchain, 70% of Fortune 500 companies still depend on COBOL and mainframe systems built in the 1960s through 1990s to process trillions in transactions daily. These legacy systems power everything from banking operations to airline reservations, insurance claims to retail inventory management. The problem? The original developers who understood these systems are retiring, taking irreplaceable institutional knowledge with them.

Enter Hypercubic, a Y Combinator-backed startup that's building what they call an "AI-native maintenance and modernization platform" for COBOL and mainframes. Founded in 2025 by Sai Gurrapu and Aayush Naik, the company is tackling one of enterprise IT's most pressing challenges: how to preserve and evolve mission-critical systems that have become increasingly opaque as their original architects leave the workforce.

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The scale of this problem is staggering. Mainframe systems process an estimated $3 trillion in commerce daily and handle 87% of all credit card transactions. Yet these systems are often treated as black boxes by modern IT departments. When something breaks, organizations scramble to find the few remaining experts who can read decades-old COBOL code and understand the intricate business logic embedded within.

Hypercubic's approach is to use artificial intelligence to reverse-engineer and document these legacy systems, creating a bridge between the past and future of enterprise computing. Their platform aims to help companies understand their existing COBOL applications, preserve the business logic embedded within them, and eventually modernize them for contemporary architectures.

The startup is already hiring for key positions as it emerges from Y Combinator's Winter 2025 batch. They're seeking a Founding Mainframe Expert with 6+ years of experience for a hybrid/remote role paying $150K-$250K plus 0.50%-3.00% equity. They're also hiring a Founding Software Engineer in San Francisco with a broader range ($125K-$200K, 0.50%-5.00% equity) that's open to new graduates.

This isn't just about preserving old code—it's about future-proofing the backbone of the global economy. As Gurrapu and Naik explain, these systems aren't just historical artifacts; they're active, critical infrastructure that needs to evolve to meet modern demands for scalability, security, and integration with contemporary systems.

The challenge Hypercubic faces is twofold. First, they need to build AI systems sophisticated enough to understand the often convoluted and undocumented logic in legacy codebases. Second, they need to convince risk-averse enterprises to trust AI with their most critical systems. It's a classic innovator's dilemma—the very organizations that need this technology most are often the slowest to adopt it.

But the market opportunity is enormous. With trillions in global infrastructure depending on these systems, and a shrinking pool of human experts who can maintain them, the demand for automated solutions will only grow. Hypercubic is positioning itself at the intersection of AI and enterprise legacy modernization, a space that's likely to see significant investment and innovation in the coming years.

For developers and engineers looking to work on meaningful problems that impact the real economy, Hypercubic offers a unique opportunity. Rather than building yet another consumer app or SaaS tool, they're working on technology that keeps the financial system, healthcare infrastructure, and global commerce running smoothly.

Learn more about Hypercubic and their mission at hypercubic.ai.