Endorsed launched as the first LLM-based AI applicant reviewer, after ChatGPT came out.

Our plan was to help recruiting teams find their top applicants faster with this next generation AI, and expand our offerings from there.

While job applications from legitimate candidates multiplied due to AI as expected, fraudulent applications went from being a non-issue to exploding to ~30% of all remote applications.

Recruiters were regularly realizing candidates were fake during interviews, on-sites, and sometimes even after they were working at the company.

These weren't bots or just dishonest individuals — they were typically government-backed fraud rings stealing IP and extorting employers, with total damages to enterprises estimated at ~$10 million each.

Recruiters became so overwhelmed by fraud that many abandoned reviewing applications entirely, focusing on sending outbound messages instead. Everyone was losing to fraud.

Applicant Tracking Systems, recruiting platforms, ID verification tools, and background screening companies tried to solve the problem, but the fraudsters quickly changed tactics to evade them. Real candidates were getting flagged as fraudulent and fake candidates were still making it through.

So we took the millions of fraudulent applicants in our database and purpose-built an AI model to detect candidate fraud, with the highest accuracy in the industry. Then we redesigned Endorsed to evolve at the pace of fraud, modeled after how payments fraud detection platforms have operated for decades.

Now, at the moment of application, recruiters and security teams can verify applicants are who they say they are, inside the tools and workflows they are already using, with no additional steps for candidates.