From side mirrors to transmissions, the countless parts pouring out of a single end-of-life car are a massive "gold mine" in themselves. But until now, this market has been thoroughly analog.
A startup has appeared in the roughly 200 trillion won global auto recycling market, which long relied on grease-stained ledgers and workers' memories, equipping it with the "digital engine" of artificial intelligence (AI) and big data. That company is Ames, led by CEO Park Won-jae. Ames is a solution corporations that identifies and verifies auto parts based on vehicle identification numbers (VINs), and it is aiming to expand into the roughly 116 trillion won global used auto parts transaction market.
In a recent interview with ChosunBiz, Park described the used auto parts market as "a market of uncertified experts." Even ordering a single BMW front bumper has different names depending on the model and year. Without three to five years of experience, it is hard to place even one part order correctly. On top of that, once you buy in this market, returns are almost impossible. The moment a headlamp costing more than 10 million won is ordered incorrectly, the loss falls squarely on repair shops or parts distributors.
In fact, it is estimated that about 70% of parts generated from end-of-life vehicles in Korea are distributed without accurate part identification information. Ames estimates that the scale of non-transaction or low-price disposals caused by this reaches about 2.5 trillion won annually.
Ames's "PartsFit" was developed to solve this problem. By entering only the VIN, users can instantly check data on about 1.43 billion items, including part numbers, compatibility, and diagrams. Ames currently holds data for 14 brands and more than 126,000 models.
Productivity gains have also been confirmed on the supplier side at scrapyards. One scrapyard processing 300 vehicles a month cut the per-vehicle part registration time from 30 minutes to 5 minutes after adopting PartsFit. It also reduced part registration staffing from 15 to 2.
Ames plans to extend its solution beyond parts management into distribution. Park believes scrapyards can be transformed into "high-margin manufacturers that disassemble cars into parts and sell them."
In Europe, used parts are priced at about 70% of new parts. In Korea, it is only 30%. Ames calculates that exporting Korean used auto parts at retail to global markets such as Europe and the United States would completely change the margin structure.
In the process of expanding into the global distribution market, the metric Park emphasizes in particular is the "return rate." For example, the average return rate in the U.S. offline auto parts market is about 22%. As cars become more complex, more parts look the same but differ in pin counts or internal programming.
While local corporations maintain the practice of "if it is wrong, just accept the return," Ames is presenting the ability to cut the return rate to around 6% as a key competitive edge. That is the average return rate in the U.S. online auto parts market.
In global markets, the strategy is to supply the solution in API form rather than as software as a service (SaaS). The judgment is that direct integration into existing platforms is more expense-efficient.
Park also expressed confidence about the expansion of electric vehicles (EVs). "Just because it is an EV doesn't mean the data-building process or difficulty changes," Park said. "In fact, in the EV market, where part unit prices are high and the need to verify repair costs is significant, the value of Ames's solution will grow." Park noted this also aligns with the potential to expand into the global repair cost verification market for insurers.
More than half of Ames's current revenue comes from its "CA" solution dedicated to domestic insurers. While it shares the same basic structure as PartsFit, AI verifies in real time whether the parts claimed during accident repair are appropriate and whether the quantities are correct. This was an area that previously relied on the experience and skill of insurance handlers.
"Until now, even if repair shops overbilled to meet the '2 million won surcharge threshold,' there was little justification to filter it out, but at one client, the misbilling rate that was 24 out of 100 cases at the start of Ames's adoption has now fallen to the 6% range," Park said. The interpretation is that the mere fact that a verification system is functioning has triggered a self-correcting effect in the market.
DB Insurance saved about 4.65 billion won in losses over 2025 through Ames's solution. The ROI (return on investment) versus solution usage expense is about threefold. The time to process loss adjustment for accident vehicles was also shortened from 49.9 minutes per case to 8.7 minutes, yielding about a 5.7-fold improvement in work efficiency.
Park said, "Ultimately, the goal is to present a 'standard plan' that everyone can transparently accept for repair cost claims." Ames is currently discussing related measures with the General Insurance Association of Korea.
For entry into the global insurance market, Ames will first leverage client cooperation. "We are discussing a method that utilizes DB Insurance's existing network," Park said, adding, "Independently, we have also completed proofs of concept (PoCs) with State Farm and Progressive, the largest insurers in North America."
Ames has raised about 9 billion won in cumulative investment. The goal is an initial public offering (IPO) in 2028. "Through 2028, expanding market share in the domestic insurance market is the top priority," Park said. "After completing Europe and North America data development within this month, we plan to begin full-scale global expansion starting in 2028."