M Agent: Recruiter Expertise Infrastructure

M Agent solves the recruiter expertise gap by giving hiring teams instant 15-year-veteran-level capability through evidence-verified assessment + 6 non-bypassable patent gates. THE PROBLEM: Recruiters need 10–15 years to develop good hiring judgment. Most teams don't have that. Traditional screening misses embodied expertise (GitHub commits, published papers, coherent work history). THE SOLUTION: M Agent extracts claims from resumes, cross-references them against embodied proof (GitHub, DOI papers, certifications, work history), then enforces integrity through 6 patented gates (coherence, temporal depth, confidence bounds, physiological evidence, logic separability, orchestration). THE MOAT: 6 IPOS patents (May 2026, $205M–$3.4B valuation). Gates are rule-based + evidence-verified (not ML-based), so they cannot be bypassed or hallucinated. Full audit trail for compliance (EU AI Act, NYC LL144, PDPA). THE DEMO: Two real scenarios show M Agent's range: • Wei Chen (clean): Traditional 50 → M Agent 87 (finds 847 GitHub commits, 2 DOI papers, 12-year coherent career). All 6 gates PASS. • Marcus Lee (fraud): Claims CTO + VP simultaneously (impossible). Says 5 patents, zero proof. Gates detect timeline overlap (C-02) and missing evidence (C-04). C-06 blocks findings until clarified. Judge Experience: 10–15 minutes → Splash page (5 min): Problem → Solution → Moat → Scenarios → Live demo (5-7 min): 3-column layout (JD | CV | Assessment) Executive view (verdict + gates) + Technical view (agentic loop + JSON) Built by: Mohamed Reezan (particpant) + Carmen Chan )absentia) (co-inventors, 6 patents filed May 2026) Track: Sovereign AI Models | Status: Production-ready, fully deployed START: https://truematch-m-agent-demo.onrender.com/index_splash.html