Labelsets

The rating standard for AI training data

41 followers

The rating standard for AI training data

41 followers

Visit website

Authentication & identity tools

•

LLM Developer Tools

•

AI Code Testing

There's no FICO, no Moody's, no Bloomberg for the datasets behind AI — just vibes and vendor claims. LabelSets is the independent rating authority. Score any dataset across 19 dimensions with 7-oracle consensus. Signed Ed25519 cert + procurement-grade PDF (SR 11-7 / EU AI Act). Open methodology paper (CC BY 4.0). Public index: 11 tickers, 263 datasets scored, 235 signed certs. Free to rate. $49 for the signed PDF.

This is the 2nd launch from Labelsets. View more

LabelSets

Launching today

The rating standard for AI training data

LabelSets LQS is the independent rating standard for AI training data. 19 dimensions, multi-oracle consensus, and a cryptographically signed certificate auditors can verify offline. Cited in SR 11-7, EU AI Act Article 10, HHS §1557, and FDA 21 CFR 11 paperwork.

Free Options

Launch tags:Developer Tools•Artificial Intelligence•Data Science

Launch Team / Built With

AppSignal — Full-stack monitoring for errors, metrics, and logs

Full-stack monitoring for errors, metrics, and logs

Promoted

Labelsets

Maker

📌

Hey Product Hunt 👋 — Alex here, solo maker. LabelSets started six months ago as a marketplace for AI training data. It taught me something I didn't expect: the bottleneck isn't supply. There's tons of training data out there. The bottleneck is that nobody can tell the good ones from the bad ones. Teams ship models trained on data they only half-understand, and the consequences show up months later in a regulator's inbox or a 10-K footnote. So I sunset the marketplace and rebuilt the whole thing as a rating authority instead FICO/Moody's/Bloomberg-shaped layer that AI training data still doesn't have. The LabelSets Quality Score (LQS) gives any dataset a 0–100 composite across 19 dimensions, with 7-oracle consensus, an open methodology paper (DOI 10.5281/zenodo.20278981, CC BY 4.0), and an Ed25519-signed certificate that auditors can verify offline. Free to rate. $49 for the procurement-grade PDF (maps to SR 11-7 / EU AI Act Art. 10). A few things I'd genuinely love feedback on today: → Does the rating-authority frame land, or does it read as "another data quality tool"? → For the /rate flow — what would you score first? → For ML/data leads in regulated industries — what would make a signed LQS cert actually usable in your model-risk review? I'll be here all day Saturday. Ask me anything — pricing, methodology, oracle architecture, the pivot, whatever. — Alex

Report

10h ago

Hi Labelsets team. I like your 19-dimension scoring feature with multi-oracle consensus. By the way, when oracles disagree strongly on a dimension, how do you handle that? Does it lower the confidence interval or trigger a re-audit?

Report

2h ago

Previous Labelsets Launches

LabelsetsThe dataset marketplace with built-in quality scores

Launched on April 10th, 2026