AI copycat dispute puts startup IP rules to the test

The dispute reveals a problem for startups: when their advantage comes from how a service works rather than the code behind it, AI tools can recreate it without leaving clear evidence of theft.

Team Easy built FinCat to streamline claims for used-car warranty insurance, connecting insurers, repair shops, and adjusters in one system. The startup says Company A, which had been a client and service provider, launched a nearly identical platform in August. Reports describe a service that matches FinCat’s screen layouts, sample text, terms of service wording, and even errors in the original version. The terms of use for Company A’s service list the same effective date as FinCat’s, not its own launch date. Team Easy also claims Company A made over 600,000 server requests in the weeks before the launch, suggesting an attempt to extract backend data.

The difficulty for Team Easy is that AI can now recreate software workflows and design without copying the source code. This makes it hard to prove theft under current rules, which often focus on code similarity. Team Easy’s CEO has said there’s little recourse beyond waiting for an investigation, and even then, the copied service can keep running.

The case reflects a wider issue in tech. AI-driven reverse engineering has become common, with tools available on platforms like GitHub to replicate software from large companies. For startups, the risk is greater: while big firms can rely on complex algorithms, smaller companies often compete on simpler but novel ideas—exactly the kind AI can mimic quickly. Team Easy’s CEO has argued that current protections don’t account for this threat.

Similar concerns have surfaced in other recent cases. When Minicor raised $3.8 million in 2026, it focused on making legacy software work with AI agents, though not specifically on IP theft. Meanwhile, Flux’s updates to track AI coding investments suggest teams are trying to measure the value of AI-assisted work, which could become harder to protect.

The outcome of Team Easy’s complaint may influence how regulators handle AI-generated copies. For now, startups might need to find other ways to safeguard their work, such as keeping key details private or moving faster than copycats. The case makes one thing clear: in a time when AI can reverse-engineer a service in weeks, a startup’s idea may no longer be secure.

Sources: mt.co.kr