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  • OmniGPT — A Decentralized AI Adaptive Layer For Global Blockchain Networks
  • Decentralized LLM-Agent Access
  • Rapid, Low-Code Deployment
  • Application Use Cases
  1. OmniZK

OmniGPT

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Last updated 1 month ago

OmniGPT — A Decentralized AI Adaptive Layer For Global Blockchain Networks

We are excited to unveil OmniGPT, an AI aggregator and unifier that provides the adaptive layer for decentralized AI applications such as AI Agents to securely transact seamlessly across global blockchain networks.

OmniGPT solves for a highly dispersed blockchain-agent-LLM landscape where AI Agents are only performing highly limited functions in specific ecosystems due to network fragmentation. By allowing the seamless transmitting of data and secure signing, OmniGPT provides the essential adaptive layer to supercharge the scope of operations that AI Agents can offer in crypto and blockchain network functions.

In addition, OmniGPT provides the core middleware for the decentralized storage and operations of open source LLMs that power these Agents.

OmniGPT is built upon the technology of OmniZK, a secure validation protocol for Bitcoin that allows developers to message complex computations and settlement outcomes between global web3 networks.

OmniGPT will be the first decentralized AI protocol to bring AI Agents and AI-powered DeFi capabilities onto the Bitcoin network.

Decentralized LLM-Agent Access

OmniGPT allow AI Agents built on open source LLMs to access and operate on the Bitcoin network, where computations and settlements can be directed exclusively by Agents operating automously using the OmniZK secure validation layer.

Rapid, Low-Code Deployment

OmniGPT Agent SDK provides for multi-chain integrations with OmniZK and existing LLMs, allowing developers to rapidly launch and operate AI Agents with minimal code required.

Application Use Cases

AI Agents operating on Bitcoin offer a wide range of possible use cases, including and not limited to prediction markets, lending, trading, privacy, data exchange and payments.