DePIN MaaS

This demo showcases how users can interact with decentralized AI agents via the DeAI Dashboard. In this scenario, the agent receives a natural language question and provides an intelligent, real-time response. All processing is performed via decentralized compute nodes, ensuring privacy, verifiability, and trustless execution—core principles of the Sight DeAI network.

This is a demo of Stocki, a third-party AI agent built for stock market analysis. In this example, Stocki analyzes Tesla (TSLA)—pulling in relevant news, summarizing potential market impact, backtesting trading indicators, and offering investment suggestions based on natural language input. Stocki can be integrated directly with the Sight decentralized AI network, leveraging distributed compute to serve users in a scalable and composable way. While this demo focuses on Tesla, the agent is designed to work with any stock or market context.

This demo features Stocki, a third-party AI agent designed to analyze market trends for digital assets and traditional stocks. In this scenario, Stocki processes Bitcoin (BTC) queries—retrieving market sentiment, summarizing recent developments, analyzing key indicators, and generating actionable insights. Stocki is fully compatible with the Sight decentralized AI network, enabling scalable and modular deployment across various user and developer ecosystems.

This demo showcases Memecoin King, a native AI agent developed by our team to explore the fast-moving memecoin ecosystem. In this example, the agent identifies trending meme tokens, analyzes performance metrics, and helps users surface early opportunities—all through a natural language interface. Memecoin King is fully integrated with the Sight decentralized AI network, enabling fast, scalable, and on-demand crypto intelligence.

This demo showcases how multiple tool nodes can seamlessly integrate into the Sight DeAI network, each offering unique capabilities—from data retrieval to real-time computation. A user initiates a query via MCP (Model Context Protocol), and the network routes the request to several decentralized nodes. Each node responds independently based on its available tools, enabling parallel feedback collection and result aggregation. This architecture empowers developers to deploy diverse tools, and allows users to query a distributed pool of intelligence—with no central coordinator.