Zypher's Crypto Economics Paper

Visit zypher.network/economics for more details.

The Zypher Network tokenomics framework is designed to power a new era of verifiable, decentralized AI Agents. As artificial intelligence shifts from experimentation to large-scale deployment, questions of trust, security, and incentive alignment have become central. Traditional AI systems operate as opaque black boxes, requiring blind trust in centralized operators, which introduces risks of manipulation, data leakage, and system failure.

Zypher addresses this “AI trust deficit” by embedding zero-knowledge proof (ZKP) technology into every layer of its infrastructure. Through protocols like Proof of Prompt (zkPrompt) and Proof of Inference (zkInference), developers and users can verify that AI Agents are operating on the correct prompts, executing inference faithfully, and producing results that have not been tampered with.

The Zypher token underpins this architecture by serving multiple roles:

• Mining Rewards & Incentives — powering the decentralized Proof of ZK Work (PoZK) network of miners who generate and validate proofs.

• Staking & Security — securing the network by aligning incentives between miners, developers, and users.

• Utility for AI Verification — enabling payments for ZK proof generation, compute resource scheduling, and privacy-preserving operations.

• Governance — empowering token holders to guide protocol upgrades, parameter changes, and ecosystem strategy.

By combining cryptographic verification with an incentive-aligned economy, Zypher Network ensures that AI Agents can be trusted without relying on centralized intermediaries. This creates a self-sustaining cycle of adoption, where greater AI Agent demand leads to more ZK proofs, deeper token utility, and stronger network security.

In the sections that follow, we outline Zypher’s token allocation model, incentive mechanisms, and economic design principles that make this possible.