
Hypercubic, a startup founded by former Apple engineers, raised $5.3 million to automate the modernization of legacy COBOL applications using AI agents.
COBOL, written in 1959, still powers more than 95% of the world's swipe transactions and ATMs, but fewer than 10% of today's COBOL engineers will remain in the workforce within five to 10 years.
The startup's AI agents map code, recover hidden business logic, generate documentation, and rewrite applications in modern languages in just a couple of months—dramatically faster than the years typically required for manual rewrites.
What happened
Hypercubic, founded by former Apple engineers Sai Gurrapu and Aayush Narik, raised $5.3 million in seed funding led by CIV with participation from Y Combinator, Afore Capital, Pioneer Fund, Multimodal Investors, and angels including Opendoor CEO Kaz Nejatian. The startup uses AI agents to map, document, and rewrite legacy COBOL applications.
Why it matters
COBOL—first written in 1959 and still supporting more than 95% of the world's swipe transactions and automated teller machines—is embedded in critical systems at banks and governments, yet 90% of current COBOL engineers are expected to retire within the next five to 10 years. Manual modernization takes years and carries massive risk; Hypercubic's agents can complete the job in just a couple of months, potentially solving a pressing crisis for financial institutions and industrial companies.
What to watch
Hypercubic is already working with one of the largest banks in Latin America and a leading Caribbean retailer serving more than 50 million customers annually. The funding will be used to expand AI agent capabilities and serve more enterprise customers.
Ask the AI about this article →
The COBOL crisis is real and growing urgent. Estimates indicate 200 billion-plus lines of COBOL code remain in production globally, primarily at banks, governments, and large industrial firms where downtime is catastrophic. The language's original developers have long since retired, and the second generation—the engineers who learned COBOL decades ago—are now aging out themselves; 90% are projected to leave the workforce within five to 10 years. Organizations know modernization is necessary but have systematically delayed it because manual rewrites are expensive, time-consuming (taking years per application), and carry extreme risk: a single undocumented change in a monolithic COBOL system can bring down critical services such as bank ledgers or government payment systems, with debugging potentially taking days.
Hypercubic's approach sidesteps this paralysis by automating the most labor-intensive and risky parts of the modernization process. Rather than hand-translating syntax, the startup's AI agents first map the entire codebase and recover the business logic buried within it—logic that was never formally documented when the code was originally written. From that recovered logic, the agents generate documentation and then produce equivalent modern code (in languages such as Java) that preserves the original system's behavior. By compressing a multi-year project into a couple of months and reducing manual risk, the startup addresses a genuine pain point for its target customers. The fact that it is already working with one of Latin America's largest banks and a major Caribbean retailer—each with millions of customers at stake—suggests the value proposition is compelling to risk-averse enterprises.
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