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🤖AI Data Labeling

Your Model Is Only as Good
as Your Annotators.

One person with 50 accounts is poisoning your training data right now. Sybil attacks on labeling pipelines are invisible — until your model ships broken.

Sybil attacks on labeling pipelines

Your inter-annotator agreement score can look healthy while one person drives 40% of labels.

1 person
can create 50+ annotator accounts and dominate your dataset
Common Mechanical Turk abuse
~30%
of crowd-labeling tasks can be submitted by repeat workers
Academic research estimates
$0
cost for a bad actor to poison your training data at scale
APTOGON analysis
∞
cost to retrain a model on corrupted labels
Industry experience

How it works

One DID per device. Multiple devices by one person form a detectable cluster.

01
📋
Annotator opens task

Your labeling platform embeds the APTOGON widget before granting access to annotation tasks.

02
✍️
Gesture verification

A unique gesture confirms a live human. Device signals prevent automation scripts from passing.

03
🔑
Unique DID issued per device

Each physical device gets one DID. One person with 10 phones = 10 flagged accounts, not 10 annotators.

04
🧮
Aggregate to person-level

Your backend can see when multiple DIDs share the same trust graph — exposing sybil clusters before they contaminate labels.

Why alternatives fall short

Nothing else ties an annotator to a physical device.

Email verificationOne person, unlimited email addresses✗
CAPTCHA on task entryConfirms human session, not unique identity✗
IP-based dedupVPNs and shared offices break this instantly✗
Qualification testsShareable answers, script-solvable✗
APTOGONDevice-bound DID — mathematically one annotator per device✓

What this means for your model

🎯
Diverse labels
Labels from genuinely different humans, not one person's bias amplified
🔬
Auditable provenance
On-chain proof of each annotator's humanity — show it to customers or regulators
💰
Fair payouts
Pay real annotators, not one person with 50 wallets gaming your incentives

Ready to trust your training data?

Start free with 1,000 verifications/month. Works with any labeling platform via API.

Other verticals:📊 Market Research👥 Communities🔗 Web3 / DAOs