Executive Summary

Recruiting teams and founders who post public roles on forums, GitHub, Twitter, Discord and similar channels are seeing a surge of AI-generated, low-signal applications that waste time and obscure genuine candidates. Small and mid-sized companies are worst affected because they often screen applications manually and lack enterprise-grade filtering. Build a SaaS anti-spam layer that filters and verifies public applicants before they hit the ATS, combining LLM-based authenticity detection, intent scoring, passive behavioral signals, and optional lightweight verifications (video snippets, micro-tasks). Deliver it as channel-specific plugins and an API that integrates with existing ATS and messaging tools to minimize recruiter and candidate friction. The addressable market is roughly $6.0B (2M businesses × $3K ACV) with a market score of 88/100 and revenue potential of 86/100, reflecting strong willingness to pay for efficiency gains. Key tailwinds—LLM-enabled mass applications, wider adoption of automated recruiting tools, and a shift to public/community hiring—make this an especially attractive moment to launch. You can stand out by focusing on channel-specific signals and a hybrid authenticity-plus-intent scoring model that goes beyond generic spam filters or built-in ATS heuristics. Expect real challenges—an arms race with generative models, privacy/regulatory tradeoffs, and the risk of false positives—but with medium competition and clear ROI for SMBs, an early, well-integrated product could capture meaningful share.

Market Opportunity

Filter and verify public job applicants to stop AI-driven spam targets a $6.0B = 2M businesses × $3K ACV total addressable market with medium saturation and a year-over-year growth rate of 12% YoY estimated for HR tech and recruitment automation (source: industry reports and vendor growth signals, e.g., LinkedIn & HRTech market analyses).

Key trends driving demand: LLM-enabled mass application generation — increases volume of low-signal applications and creates demand for authenticity and intent scoring.; Adoption of automated recruiting tools — hiring teams are already using AI-driven screening, which lowers adoption friction for a specialized anti-spam layer.; Shift to community hiring and public posts — startups and remote teams increasingly hire from public forums, making channel-specific tooling more valuable.; Richer public developer signals — accessible data from GitHub, package managers, and public contributions improves ability to verify candidate authenticity..

Key competitors include Humanly, Greenhouse, Clearbit.

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Filter and verify public job applicants to stop AI-driven spam

Executive Summary

Market Validation

Market Opportunity

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