What is Alaya Governance Token (AGT)?

Deep Dive

1. Purpose & Value Proposition

AGT powers a decentralized network where users contribute labeled data (like images or sensor readings) to train AI models. It solves two critical AI challenges:
- Data scarcity: Incentivizes crowdsourced data collection via token rewards
- Quality control: Uses staking mechanisms to deter low-quality submissions – users risk losing AGT stakes if they submit faulty data

By tokenizing AI models, developers can crowdfund training efforts through AGT staking pools, creating a circular economy where contributors share in model success (Alaya AI documentation).

2. Technology & Ecosystem Fundamentals

The platform employs two interconnected systems:
- Tradeable NFTs: Grant access to training tasks and reward tiers (upgradable using AGT)
- Wallet-bound Medallion NFTs: Act as skill certifications for specialized data labeling tasks

This structure enables:
- Automated task distribution based on user expertise
- AI-powered quality checks on contributed data
- Integration with BNB Chain for scalability, evidenced by its participation in Binance’s MVB program

3. Tokenomics & Governance

AGT serves three primary functions:
1. Staking: Secure network participation and earn model training rewards
2. Governance: Vote on protocol upgrades and data labeling standards
3. NFT Enhancement: Upgrade task-access NFTs to unlock premium rewards

The tokenomics integrate AIA points (non-tradable effort tokens) that convert to AGT during redemption events, creating a dual-layer incentive system.

Conclusion

AGT anchors a decentralized ecosystem where contributors, AI developers, and validators collaborate to build better AI models through structured incentives. By blending gamified data collection with blockchain-based governance, it reimagines how training data is sourced and validated in Web3.

Could Alaya’s model for community-sourced AI training data scale to challenge traditional centralized data aggregators?