# Participants and Roles

There are three main actors in the Reppo ecosystem:

1. **Publishers, or Data Contributors**: Anyone with raw training data.

This can include vibe-coded apps, AI agents, videos, images, websites, and written work.

Unlike other platforms, Reppo does not create tasks centrally. Instead, publishers pay to publish raw data into relevant datanets of their choice and bet on their own originality and quality.

This avoids repetitive tasks, over-rewarding the same type of content, and extra validation overhead.

2. **Voters, or Domain Experts:** Active participants in 48-hour prediction markets who lock REPPO to receive veREPPO. They express subjective preferences on raw data, back those preferences with economic stake, and provide the network's curation layer.
3. **Datanet Owners**: Datanets are RL environments tailored to specific AI training data domains. Individuals and enterprises can launch their own datanets and create datasets by incentivizing publishers and voters to generate and label domain-specific AI training and evaluation data.

In the network's genesis phase, the Reppo Foundation stewarded data monetization and used trading revenue proceeds for buybacks that accrued value to the ecosystem.

In Reppo V2, datanet owners take full ownership of their P\&L and decentralize data generation and monetization. This removes much of the traditional complexity around data discovery and consumption for independent developers and enterprises, and streamlines how value is created and captured across the ecosystem.


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