legal decisions.
financial recommendations.
AI hallucinations in production
AI error in regulated industries
expert verification via API
But the risky ones do.
Companies send AI outputs through our oversight API. Our risk engine evaluates each one against policy rules and risk triggers. Low-risk outputs are cleared instantly. High-risk outputs are escalated to domain experts.
Oversight engine +
expert network +
audit trail.
POST /api/v1/verify
{ "output": "Take 500mg vitamin C daily",
"domain": "healthcare" }
// Instant response — $1.50
{ "status": "cleared",
"risk": { "level": "low", "score": 0.05 },
"audit": { "method": "policy_risk_assessment",
"cleared_at": "2026-04-23T..." }
}POST /api/v1/verify
{ "output": "BPC-157 is safe with warfarin",
"domain": "healthcare",
"urgency": "realtime" }
// Escalated to expert — $30
{ "status": "escalated",
"risk": { "level": "high", "score": 0.72,
"triggers": ["domain keywords: 2",
"negated safety claim"] },
"poll_url": "/api/v1/reviews/abc123" }
// Expert response (3 min later)
{ "verdict": "incorrect",
"correction": "Bleeding risk with
anticoagulants. Not recommended.",
"expert": "MD, Internal Medicine" }2x faster.
When an expert claims a review, our AI pre-screens the output before they see it. It highlights red flags, suggests a verdict, and drafts a correction. The expert confirms, adjusts, or overrides — cutting review time from 5 minutes to 2.
unfair advantage.
We recruit domain experts the same way we built a 25+ physician pipeline for Pepti — Indeed, LinkedIn, professional networks. Doctors, lawyers, CPAs, and engineers want flexible side income. We give them 2-minute reviews they can do from their phone between patients or cases.
a defensible asset.
Every expert review generates a data pair: what the AI said vs. what the expert corrected. Over time, this becomes the largest dataset of verified AI accuracy across regulated domains. That data is a product in itself.
doesn't exist yet.
across industries.
EV applies the same oversight architecture across domains where AI mistakes carry legal, financial, or safety consequences.
Lending, education, government, biometrics, and critical infrastructure expand as regulation catches up.
Built the entire [ev] platform from scratch — API, expert dashboard, AI-assisted review system, admin tools, client onboarding, landing page.
Previously built Pepti — AI-native telehealth platform with 107 products, 24 AI features, and a physician network including a CMO from Hims & Hers.
Recruited 25+ physician candidates from a single Indeed post. Same recruiting ability powers expert supply.