Back to Home

Why Centaur

The industry default? Spend big on expert opinions. But there's a smarter way: collective intelligence. Just as prediction markets aggregate many perspectives to outperform individual experts, Centaur blends crowds, experts, and AI to achieve higher accuracy at lower cost.

Don't just take our word for it. This playground is powered by a real image classification dataset with actual opinions from experts, crowd labelers, and AI. What you see is what you get.

Your Mission

Total Budget

Cases to Annotate

Labeler Types

Optimize Your Annotation Strategy

Allocate your budget across different labeler types to maximize quality

Adjust Labeler Mix

Allocate budget to each labeler type to maximize your coverage and accuracy.

Expert #1

$65/opinion • 85% accuracy

Expert #2

$45/opinion • 80% accuracy

Expert #3

$55/opinion • 83% accuracy

Wisdom of the Crowds

Collective intelligence

$0.25/opinion • 30% accuracy (single opinion average)

Opinions per case: 0

Aggregating many opinions from our crowd can produce more accurate answers than any single expert.

LLM Labeler

$0.1/opinion • 43% accuracy

Fixed cost of 2 opinions per case when enabled: $400.

Total Allocation:

Accuracy

Coverage

Cost

Understanding the Chart

The purple line represents the Centaur Way – the optimal accuracy achievable at any given budget. Your goal is to get as close to this frontier as possible.

Accuracy vs Cost

Your attempts plotted on the optimization space

Your Attempts (0)

Saved experiments

Adjust the sliders and save an attempt to see it here.

Ready to optimize your data annotation?

Schedule a demo to see how Centaur.ai can automatically optimize your annotation workflow