Hypercubic Raises $5.3 Million Seed To Turn Mainframe Modernization Into A Software-Driven Process

Hypercubic has raised $5.3 million in seed funding to build an AI-powered platform that automates significant portions of mainframe modernization projects. The round was led by CIV, with participation from Y Combinator, Afore Capital, Multimodal Ventures, Pioneer Fund, Epsilon Ventures, Unpopular Ventures, and other investors.

Angel investors include Opendoor CEO Kaz Nejatian, Walmart Labs co-founder Venky Harinarayan, Coinbase and Pinterest board member Gokul Rajaram, Privy co-founder Henri Stern and Infisical co-founder Tony Dang.

Hypercubic is targeting some of the oldest and most critical software still operating across banks, insurers, governments, airlines, retailers and other large enterprises.

Many of these mainframe applications contain decades of business logic, operating knowledge and edge cases that can be difficult for organizations to reconstruct.

Traditional modernization projects can take years, involve large engineering teams and cost tens of millions of dollars.

The process requires enterprises to understand existing applications, recover undocumented business logic, rewrite systems, migrate data and verify that new software behaves correctly without disrupting operations.

Hypercubic believes advances in AI reasoning models make it possible to convert more of that work from a labor-intensive consulting and engineering process into repeatable software.

The company is building a platform designed to understand, rebuild and verify mainframe applications.

Hypercubic said early customer deployments are already demonstrating that portions of the modernization lifecycle can be completed substantially faster and at lower cost than traditional methods.

The company was founded approximately a year ago and is now using the seed financing to expand its team and technology.

Its longer-term ambition is to become infrastructure through which a meaningful share of the world’s legacy critical software can be understood and rebuilt.