Catch risky AI outputs
before they ship.

Every output assessed. Low-risk cleared instantly. High-risk escalated to experts. Full audit trail.

See live demoGet API access
$1.50
Auto-clear (low risk)
$8-75
Expert review (high risk)
< 2 min
Expert review time
EV
Oversight
Overview
Reviews
Audit
Live
Cleared
847
Escalated
0
Blocked
3
Incoming
High riskHealthcare
0.78
TRT has no cardiovascular risks and is safe for all men...
Low riskFinance
Cleared
Diversification helps reduce portfolio risk over time...
What is EV

An oversight API that sits between your AI and the real world.

Before your AI output reaches a patient, client, customer, or employee — it passes through EV. Our risk engine evaluates it against policy rules and domain-specific triggers. If it's safe, it clears instantly. If it's risky, a credentialed expert reviews it. If it's dangerous, it gets blocked.

Every output — whether cleared, reviewed, or blocked — gets a documented audit trail with timestamps, risk scores, trigger details, and reviewer credentials. That's the record your compliance team needs.

What it replaces
Manual spot-checking
Teams review 5% of outputs and hope the other 95% are fine.
AI-to-AI checking
Using one model to verify another. Regulators don't accept this as human oversight.
Hiring internal reviewers
$500K+/year for a team that still can't cover every domain or every shift.
Doing nothing
Ship and pray. Until a wrong output costs you $2.4M or a regulatory fine.
The cost of a bad output

One wrong message. Real consequences.

The cost isn't just the message — it's the downstream harm, rework, liability, and loss of trust it creates.

Low stakes
Refund issued. Customer lost. Support escalation. Manual rework. Supervisor time wasted.
High stakes
Legal exposure. Regulatory scrutiny. Discrimination complaint. Unsafe patient outcome. Compliance violation.
Systemic failure
Reputational damage. Multi-million dollar control failures. Enforcement actions. Loss of operating license.
$4.44M
Average data breach cost. Ungoverned AI makes it worse.
IBM 2025
$193K
FTC fined DoNotPay for misleading AI claims.
FTC 2024
Active
CFPB warned chatbot failures create consumer harm in finance.
CFPB
Active
EEOC says AI hiring decisions must comply with discrimination law.
EEOC
Who it's for

If your AI touches health, money, jobs, or legal rights — you need oversight.

Health AI companies
Clinical decision support tools, symptom checkers, medication recommendation engines, telehealth AI, drug interaction checkers. Your AI gives medical advice — if it's wrong, someone gets hurt.
Companies like: Glass Health, Counsel Health, Hippocratic AI
Legal AI tools
Contract review platforms, legal research assistants, compliance checkers, immigration tools. Your AI interprets law — if it's wrong, someone loses a case or signs a bad contract.
Companies like: Spellbook, Luminance, EvenUp
Financial AI
Investment recommendation engines, credit scoring, tax preparation AI, portfolio analysis. Your AI handles money — if it's wrong, someone loses their savings.
Companies like: Rogo, TaxGPT, FP Alpha
Hiring AI
Resume screening, candidate scoring, performance review tools, termination recommendation systems. Your AI makes career decisions — if it's biased, you get sued.
Companies like: Any company using AI in HR
Insurance AI
Claims processing, risk assessment, pricing algorithms, underwriting AI. Your AI decides coverage — if it's discriminatory, regulators come knocking.
Companies like: Any insurer using AI
Enterprise copilots
Internal AI tools that draft emails, analyze data, make recommendations to employees. If your copilot gives bad advice, your company acts on it.
Companies like: Any company deploying internal AI
The risk engine

Not a keyword filter.
A policy-based assessment.

Every output is evaluated against multiple layers of analysis. The engine doesn't just look for bad words — it understands the context of what's being said and why it might be dangerous in that specific domain.

Absolute safety claims
Catches statements like "completely safe," "no risk," "100% effective" — almost always wrong in medical, legal, or financial contexts.
Domain-specific triggers
Healthcare: drug interactions, contraindications, dosing. Legal: jurisdictional claims, enforceability. Finance: suitability, tax advice, guaranteed returns.
Missing context
Flags universal recommendations that ignore patient history, investor profile, jurisdictional differences, or individual circumstances.
Policy rules
Configurable per-client. Always-review mode, risk-based routing, blocklists, domain-specific escalation rules. You control what gets flagged.
Negated safety claims
"No cardiovascular risks" + "TRT" = instant escalation. The engine understands when negation + medical term = danger.
Real example
AI output submitted
“Testosterone replacement therapy has no cardiovascular risks and is completely safe for all men over 30 regardless of their medical history.”
Risk engine assessment
High riskScore: 0.78
Unsafe blanket reassurance
Absolute safety language detected
Cardiovascular-risk terminology
No patient-specific context
Decision
Escalated to expert review
Expert verdict (1m 47s)
RejectedMD, Board Certified Internal Medicine
Corrected output
Testosterone replacement therapy carries documented risks, including potential cardiovascular and thrombotic complications. Treatment decisions should be based on individual medical history, risk factors, and clinician oversight.
Audit trail

Every output. Every decision. Documented.

When a regulator asks “how do you ensure human oversight of your AI?” you point them here. Every output that passes through EV generates a complete record.

Audit Record #ev-2026-04-23-00847
Timestamp2026-04-23T14:32:07.412Z
ClientGlassHealth Inc. (client_a8f2...)
DomainHealthcare
Risk levelHigh
Risk score0.78
Triggers4 — Unsafe blanket reassurance, Absolute safety language, Cardiovascular-risk terminology, No patient-specific context
Escalation rationaleMedical safety claim + treatment recommendation + universal statement without patient context
Policy moderisk_based
Policy decisionEscalated to expert review
ReviewerDr. [redacted], MD, Board Certified Internal Medicine
Reviewer credential verifiedYes — NPI on file
VerdictRejected
Clinical reliabilityLow
Review time1m 47s
Correction providedYes — see corrected output
Final dispositionExpert-corrected response approved for delivery
Delivery statusApproved for end-user delivery
Cost$30.00

Audit records retained for 7 years. Exportable. API-accessible.

Pricing

Two paths. You only pay when we check.

Every AI output you send goes through our risk engine. If it's safe, you get instant confirmation. If it's risky, a real expert reviews it. No monthly fee. No minimum.

Safe output? Cleared instantly.
Your AI output passes the risk check with no issues. No human needed. You still get a documented audit trail proving it was assessed.
$1.50
per output checked
Risk engine scans for dangerous claims
Checks domain-specific triggers
Evaluates against your policy rules
Returns instantly
Full audit trail documented
No expert involved — all automated
Risky output? Expert reviews it.
Your AI output triggered risk flags — a credentialed expert reviews it, corrects it if needed, and approves a safe version before it reaches your user.
$8-75
per output — depends on urgency
Everything in the risk check
Escalated to a credentialed expert
AI pre-screens and highlights issues
Expert provides verdict + correction
Reviewer credentials on record
Average review time under 2 minutes
Standard
$8
< 24 hr
Fast
$15
< 1 hr
Realtime
$30
< 5 min
Critical
$75
< 2 min

Blocked outputs are free. 20 free reviews to start. Enterprise plans available.

How it works

One API. Three outcomes.

Your AI output
POST /api/v1/verify
Risk Engine
Policy rules · Domain triggers · Risk patterns
Cleared
$1.50
Instant
Low-risk. Approved by policy. Full audit trail logged.
Escalated
$8-75
Under 2 min
High-risk. Expert reviews, corrects, approves. Audit trail.
Blocked
$0
Instant
Dangerous. Rejected with risk report. Never reaches user.
Every output gets an audit trail — cleared, reviewed, or blocked.
The product

Oversight engine +
expert network +
audit trail.

+ Policy-based risk engine with configurable rules and triggers
+ Auto-clear low-risk outputs instantly ($1.50)
+ Escalate high-risk outputs to credentialed experts ($8-$75)
+ Block dangerous content before it reaches anyone
+ AI pre-screens flagged outputs — experts review in under 2 min
+ Webhooks for real-time delivery
+ Configurable modes: always-review, risk-based, or auto-clear
+ Documented audit trail on every output
Cleared — low risk
POST /api/v1/verify
{ "output": "Take 500mg vitamin C daily",
  "domain": "healthcare" }

{ "status": "cleared",
  "risk": { "level": "low", "score": 0.05 },
  "cost": "$1.50",
  "audit": { "method": "policy_risk_assessment",
    "cleared_at": "2026-04-23T..." } }
Escalated — high risk
POST /api/v1/verify
{ "output": "TRT is safe for all men over 30",
  "domain": "healthcare",
  "urgency": "realtime" }

{ "status": "escalated",
  "risk": { "level": "high", "score": 0.78,
    "triggers": ["Unsafe blanket reassurance",
      "Absolute safety language"] },
  "cost": "$30.00",
  "poll_url": "/api/v1/reviews/abc123" }
Domains

Built for domains with elevated oversight requirements.

Same oversight engine. Different policy layers, experts, and risk triggers by domain.

Healthcare
Clinical decision support. Medication safety. Treatment recommendations.
Finance
Credit scoring. Investment analysis. Compliance-sensitive recommendations.
Legal
Contract review. Case analysis. Regulatory interpretation.
Hiring / HR
Candidate screening. Performance reviews. Termination decisions.
Insurance
Risk assessment. Claims analysis. Pricing decisions.
Enterprise Copilots
Internal AI tools making business-critical recommendations.

Lending, education, government, biometrics, and critical infrastructure expanding as regulation grows.

Why now

Oversight requirements are accelerating.

Regulation is expanding
FDA, FINRA, FTC, NYC LL144, Colorado AI Act, EU AI Act — all moving toward requiring documented human oversight for high-stakes AI.
AI is deploying faster
Every company is shipping AI into production. The faster they deploy, the more oversight infrastructure they need.
No standard solution exists
Companies are either building expensive internal teams or hoping for the best. EV is purpose-built for this.
$16.4B
Human-in-the-loop AI market by 2030
$5.8B
AI governance market by 2029
77%
Of enterprises worried about hallucinations
$2.4M
Average cost of a major AI error
Beyond output checking

A full oversight operating system.

EV doesn't just check AI outputs. It governs everything customer-facing — whether it came from AI, an employee, or both. Actions, messages, and decisions all flow through the same oversight engine.

Conversation Oversight
Check any customer-facing message before delivery — whether written by AI, an employee, or both. Same risk engine. Same audit trail.
AI, human, and hybrid messages
Action Approvals
Not just what AI says — what it does. Should this agent send a refund? Approve a claim? Change a dosage? EV gates the action before it executes.
Refunds, claims, appointments, account changes
Bring Your Own Reviewers
Use your own staff as reviewers — your doctors, lawyers, compliance officers. Or use our expert network. Or both.
Internal teams + EV experts
Policy Builder
Set your own rules. Always escalate medication dosing. Auto-clear general wellness. Block anything mentioning suicide. You control what gets flagged.
Custom rules per workflow
Escalation Ladders
AI pre-screens first. Then junior reviewer. Then senior. Then compliance officer. Multi-tier chains with auto-escalation timeouts.
AI → Junior → Senior → Compliance
Post-Delivery Monitoring
Track patterns in outputs that made it through. Detect model drift. Flag recurring issues. Get incident alerts before they become crises.
Pattern detection + incident response
Analytics & Scorecards

See where your AI fails.
Fix it before it matters.

Every output, action, and conversation that flows through EV generates data. We turn that into scorecards, failure mode analysis, and risk trends — so you know exactly where your AI is weakest.

+ Risk distribution across all outputs and actions
+ Verdict breakdown — correct, partial, incorrect, unsafe
+ Domain-level performance scorecards
+ Model drift detection over time
+ Cost analysis — actual spend vs all-human review estimate
+ Common failure patterns by domain and model
Sample analytics response
GET /api/v1/analytics

{
  "overview": {
    "totalOutputsProcessed": 12847,
    "totalActionsProcessed": 3291,
    "totalIncidents": 7,
    "unresolvedIncidents": 2
  },
  "reviews": {
    "verdicts": {
      "correct": 8421,
      "partially_correct": 2103,
      "incorrect": 847,
      "unsafe": 31
    }
  },
  "cost": {
    "totalSpent": "$18,420.00",
    "estimatedSavings": "$142,800.00"
  }
}
System of record

The compliance database your regulators want to see.

Every output, every decision, every review, every policy — stored, searchable, exportable. When a regulator asks how you oversee your AI, you point them here.

What was generated
What source produced it
Why it was flagged
Who reviewed it
What they changed
What was finally sent
What policies were active
What model/version produced it
Timestamps on every step
Reviewer credentials
Escalation history
7-year retention

Exportable. API-accessible. Built for audits.

Start catching risky outputs today.

Free to sign up. 20 free reviews to test. No commitment.

Get API accessSee live demo
$1.50 auto-clear$8-75 expert reviewFull audit trailAPI docs included
For domain experts

Get paid to review AI outputs.

Doctors, lawyers, engineers, analysts — AI pre-screens every output, you make the final call. Under 2 minutes per review. Work from anywhere.

$3-40
Per review
< 2 min
Review time
Weekly
Payouts
1099
Flexible
Apply nowLearn more