Recently, I’ve looked into many new blockchain projects, and Kite stands out as a bit different. It doesn’t follow the old path of "another public chain," but instead aims to build infrastructure supporting the underlying economic system based on actual needs of AI agents.

In terms of positioning, Kite calls itself the "first AI payment blockchain." Essentially, it has built an aggregation platform where users can access multiple AI agents through a single entry point to perform real-world operations like ordering food and shopping. On the surface, it looks like an AI aggregator, but the real difference lies in using blockchain behind the scenes for identity verification, payment clearing, and permission governance.

The technical implementation is quite meticulous. Kite chose an EVM-compatible Layer 1, so existing development tools and ecosystems can be used directly, avoiding reinventing the wheel. To accommodate the frequent interactions of AI agents, it has also optimized for performance. I particularly appreciate its three-layer identity system—separately managing users, agents, and sessions—allowing for finer permission control and significantly reducing the risk of identity confusion.

What’s more interesting is that it assigns verifiable encrypted identities to AI-related entities (models, agents, data sources) and supports complete on-chain traceability of their behavior. In an era where the authenticity of AI-generated content is hard to verify, this traceability system becomes a practical governance tool. Coupled with programmable governance modules, it can set constraints on agent permissions and fund usage—effectively defining clear boundaries for autonomous actions.

On the payment layer, Kite aims for instant confirmation and nearly zero transaction fees for value transfer, with native support for stablecoin settlements. According to public data, its on-chain costs are extremely low, confirmation speeds are fast, and TPS has already reached the million-level mark. This performance effectively addresses the pain points of high-frequency AI service interactions.