Introduction

Background Artificial Intelligence (AI) now underpins everything from conversational assistants to real-time video generation. Yet the infrastructure that powers these technologies is concentrated in a small number of players: OpenAI (ChatGPT), Google (Gemini), Microsoft (Azure), and a few others. Their closed servers process petabytes of user data, creating a single point of control and a single point of failure. End-users remain largely blind to how, where, and for how long their information is stored, audited, or monetised. This centralisation raises clear concerns over privacy, censorship, data leaks, and fair access to AI innovation.

Veil Protocol counters these risks by deploying a custom TAO subnet on the Bittensor blockchain. Computation and model storage are distributed across independent miners and validators, who earn $TAO for their contributions. On top of this substrate, the Tennet™ application delivers a range of configurable AI agents (chatbots, media generators, autonomous task bots, and personal knowledge avatars), while giving users precise control over data retention, encryption, and network preferences. The result is a censorship-resistant AI infrastructure where value flows to the participants who run it.

Objectives

• Decentralization: Use the Bittensor network to distribute model training, inference, and data storage, eliminating single points of failure.

• User Privacy: Keep sensitive data local whenever possible and enforce end-to-end encryption and zero-knowledge proofs when data must travel.

• Scalability: Design a subnet architecture that scales along with miner supply and rising AI workloads.

• Governance: Empower the community through Veil DAO, enabling token-weighted voting on protocol upgrades, economic parameters, and feature roadmaps.

• Incentive Alignment: Reward miners, validators, and stakers in $VEIL and $TAO, ensuring that those who secure and improve the network share directly in its growth.