Most AI companies get human feedback from anonymous crowds or opaque managed services. Kelva is different — a transparent marketplace of credentialed doctors, lawyers, and researchers, accessible via API.
Millions of unverified workers completing tasks for cents. Fast and cheap — but you have no idea who's rating your medical AI.
Premium providers with expert annotators — but you can't see who they are, verify their credentials, or access them directly.
Credentialed professionals with verified licenses, visible accuracy scores, and full audit trails — accessible via self-serve API.
Enterprise customers control which tiers can review their data. Need only Tier 1 board-certified specialists for clinical AI? Set the minimum credential and Kelva routes accordingly. Every audit trail shows the validator's tier transparently.
Doctors, lawyers, researchers, and journalists — earn $9 to $40 per task evaluating AI outputs in your field.
Submit AI outputs via API, specify the credentials you need, and get transparent evaluations back within hours.
Every task completed adds to a proprietary map of who is accurate at what. Over time, Kelva knows that a specific cardiologist in Chicago is the most reliable reviewer of oncology AI responses.
This graph is the real product. It compounds with every task, gets smarter with every evaluation, and cannot be replicated by competitors starting from zero.
The Intelligence Graph transforms Kelva from a marketplace into infrastructure — the longer you use it, the better your results, the harder it is to leave.
Board-certified physicians evaluate clinical AI outputs. Full audit trail for FDA compliance and institutional review.
Bar-admitted attorneys review AI-generated contracts and legal research. Credentialed validation for malpractice-sensitive products.
Credentialed journalists flag hallucinations, verify claims, and evaluate AI-generated content against editorial standards.
CFA charterholders review AI-generated investment analysis, risk assessments, and regulatory filings for accuracy.
University faculty and PhD researchers validate AI outputs. Institutional partnerships with leading research universities.
Domain experts stress-test AI models for hallucinations, bias, and safety failures with structured adversarial evaluation.
| Batch | Domain | Tasks | Progress | Status |
|---|---|---|---|---|
| batch_8f2a9x | Cardiology | 250 | Complete | |
| batch_3k7mzp | Contract Law | 180 | In Progress | |
| batch_9w4htn | Pharmacology | 500 | In Progress | |
| batch_2p8qvr | AI Safety | 100 | Matching |
| Validator | Institution | Tasks | Accuracy | Score |
|---|---|---|---|---|
| Dr. Priya Sharma | Columbia Medical | 1,583 | 98.2% | 96 |
| Dr. Sarah Chen | Mount Sinai | 1,247 | 97.1% | 94 |
| Dr. Ravi Mehta | Johns Hopkins | 2,104 | 95.7% | 93 |
| James Whitfield, JD | Columbia Law | 893 | 94.8% | 91 |
| Dr. Marcus Williams | NYU Langone | 892 | 93.5% | 91 |
| Domain | Accuracy | Tasks |
|---|---|---|
| Cardiology | 97.1% | 847 |
| Pharmacology | 95.7% | 289 |
| General Medicine | 93.2% | 111 |
Get an API key and start submitting tasks in minutes. No sales calls, no contracts, no minimums.
See exactly who evaluated your data — their name, credentials, accuracy history, and Kelva Score. No anonymous labor.
Specify board-certified, bar-admitted, PhD, or custom requirements. Only matching validators see your tasks.
Full audit trail for FDA, EU AI Act, and SOC 2. Every evaluation traceable to a verified professional.
For teams exploring credentialed feedback
For teams integrating into their pipeline
For AI labs with custom requirements
All data encrypted in transit (TLS 1.3) and at rest (AES-256). Your AI model outputs are never exposed to unauthorized parties at any point in the evaluation pipeline.
Every evaluation is traceable to a verified professional — who reviewed, when, what credentials they hold, what they said. Built for FDA submissions and EU AI Act documentation requirements.
Enterprise customers can restrict access to pre-approved reviewers only. Your data is never seen by anyone you haven't vetted — full control over who touches your model outputs.
Every validator signs a binding non-disclosure agreement during onboarding. Storing, screenshotting, or redistributing AI outputs is a contractual violation with legal consequences.
Credentials are verified against issuing authorities — state medical boards, bar associations, university registrars. No self-reported expertise. Annual re-verification on all active validators.
Hosted on SOC 2 certified cloud infrastructure. Role-based access controls, automated vulnerability scanning, incident response procedures, and 99.9% uptime SLA.
Before Kelva, I built a media fact-checking platform for EU newsrooms — a system that verifies claims, scores source credibility, and flags AI-generated misinformation. That platform is currently in pilot with European news organizations.
Building that product taught me three things: how to verify human credentials at scale, how to build trust scoring systems that get smarter over time, and how to sell verification products to demanding institutional customers. Those are exactly the three capabilities Kelva requires.
The fact-checking platform isn't a dead project — it's proof of concept. The validator network architecture, the trust scoring logic, and the API infrastructure translate directly into the RLHF marketplace. I'm not starting from zero. I'm expanding from a working base.
Join the founding cohort of AI companies who demand transparency in human feedback — and the credentialed professionals who provide it.