Holdstation, a popular Web3 wallet, has introduced A(i)gentFi, an innovative AI agent platform built on the ZKsync network. This platform is designed to create, manage, and monetize AI agents, further integrating artificial intelligence into the blockchain.

What is A(i)gentFi?

A(i)gentFi is a “one-stop shop” on ZKsync dedicated to the creation and development of AI agents. These AI-powered entities can execute complex tasks such as trading, analyzing markets, and creating content autonomously, without human intervention. The platform prioritizes real-world applications, including DeFi automation, yield farming, and tokenized AI ownership.

A(i)gentFi’s Key Features

A(i)gentFi employs several key features to streamline complex processes and reward participants:

  • DeFi automation to simplify tasks
  • A fee-sharing mechanism to incentivize participants
  • A tokenized AI ownership system, allowing users to co-own AI agents on ZKsync

$2 Million Grant to Support AI Innovation

To drive more developers to use the AI agent platform, Holdstation is launching a $2 million grant to support developers, DAOs, and creators in building AI and blockchain projects on A(i)gentFi. The grant will provide technical assistance, including infrastructure, tools, and expert guidance, as well as financial support in the form of Holdstation’s governance token, HOLD.

The Growing Presence of AI in Crypto

AI technology is still in its early stages of entering the crypto sphere. However, with the rise of AI platforms, this sector is projected to grow significantly. An analysis showed that AI-integrated crypto projects currently make up only 1% of the total crypto market cap, but this number is expected to increase by as much as 10x.

Recent AI Developments in Crypto

Other notable developments in the AI-crypto space include:

  • KaJ Labs’ $100 million investment in building advanced AI solutions within the XRP ecosystem
  • Tools for Humanity’s partnership with AI startup Modulus Labs to improve security for its layer-2 network World

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