Author: Sam Ruskin, Messari Research Analyst; Translation: 0xjs@Jinse Finance
Virtuals is a platform for creating, trading, and deploying AI agents, which has achieved a growth of 400% in less than a month and has become the largest protocol on Base. Virtuals was once labeled as another memecoin launch platform, but now it has sparked discussions about the importance of agent frameworks and the power of agents to change how we interact on the chain.
The largest Virtual intelligent aixbt has over 140,000 fans on X as of December 16, with a market value of 2.5 billion dollars. While high-profile intelligent agents like aixbt and Luna have captured people’s attention, many other Virtual intelligent agents are dealing with a variety of professional use cases. Below, we explore some noteworthy examples.
Source: virtual protocol
Type: productivity
Key Features: VaderAI positions itself as a leader in the AI economy by managing AI agent investments in DAOs. As the first AI agent token for autonomous trading, it is responsible for research, strategy simulation, and on-chain execution. The upcoming AI agent token investment DAO will allow both humans and AI agents to participate, requiring a $VADER pledge for access. In the long run, VaderAI aims to establish a dedicated network of investment DAOs, each managed by a tailored AI agent.
Related links: VaderAI on Virtuals | X | Documentation
Type: Information
Key Features: Seraph is an autonomous AI agent built on the Bittensor decentralized intelligence network, designed to provide accurate and verifiable analysis. It uses the Virtuals framework to manage multiple specialized AI roles that collaborate to cross-reference and validate data, ensuring reliable insights. By leveraging the deepfake detection model Bittensor Subnet 34 (BitMindAI), Seraph can provide authentic and verifiable analysis.
Related links: Seraph on Virtuals | X | Documentation
Type: On-chain
Key Features: PondHub, launched by Pond, is a technology stack that developers can use to tailor tokenized intelligent agents for various use cases. Pond aims to make model ownership and creation easier by lowering the barrier to entry for encrypted AI. Pond is building a model layer for developers to collaborate on creating, owning, and monetizing native encrypted AI models, and providing model development guidance, resources, and infrastructure. The company recently completed a $7.5 million seed round led by Archetype.
Related link: PondHub on Virtual | X | document