What is it?

It is a reliable artificial intelligence agent, relying on verified intelligence levels.

What are we doing now?
Our verification network empowers the next generation of autonomous agents, ensuring that their output results are accurate, resilient to errors, and can operate without the need for trust.

We provide a verification infrastructure that can be accessed by the agency framework to overcome cognitive bias issues, ensuring that autonomous operations can scale safely without relying on human intervention.

What have we accomplished?
Here are some examples of frameworks and teams built using our API👇

SendAI

Leverage our distributed validation infrastructure to ensure that agents built on the Solana Agent Kit produce trusted outputs. SendAI significantly enhances the reliability of on-chain autonomous operations.
Both parties are committed to creating a complete on-chain autonomous agent that operates independently without human intervention.

ZerePy from the Zerebro team

Integrate our consensus mechanism into ZerePy - a Python agent framework that achieves verifiable proxy outputs on Web3 and social platforms through modular connectors.
This collaboration has strongly advanced our vision of achieving "verifiability goals" on a fully digital platform.

OpenLedger

Contributed cutting-edge benchmarking and evaluation solutions for distributed AI agents, enhancing the robustness of our verification and testing layer.
Their expertise has accelerated our process of establishing reliability standards for general AI.

Eliza OS

As a native Web3 intelligent agent operating system, it has over 15,000 GitHub stars. It offers multi-model compatibility and a scalable architecture, and enhances the determinism of autonomous AI operations by integrating our validation core module.
Both parties jointly promote the development of a truly "trustless" next-generation AI system.

ARC

Our trust layer has been integrated into the open-source large language model framework Rig written in Rust, serving over 2.5 million users and achieving a reduction of over 90% in error occurrence rates during more than one million inferences per day.
This collaboration demonstrates the scalable prospects of achieving zero-error AI at a production-level scale.

From gaming to social applications, from native blockchain to multimodal scenarios, our native integration with diverse frameworks ensures that—regardless of where the agents are deployed, the verification capabilities are always present.

We will continue to update relevant information later.