Real World Asset (RWA) tokenization is rapidly becoming one of the most compelling trends in blockchain. As of mid-2025, over $8 billion worth of RWAs—ranging from U.S. Treasury bonds, gold, to real estate—have already been tokenized and deployed across major chains like Ethereum, Polygon, and Solana (source: rwa.xyz, 2025 Q2 report).

Each month, StaFi DAO will share a financial and data report with the community to keep everyone informed.

As Q3 2025 begins, the StaFi roadmap focuses on launching Liquid Staking Vaults (LSV) and expanding the SubDAO ecosystem. In alignment with these priorities, a potential listing of $FIS on Hyperliquid, a high-performance, on-chain order book exchange — is currently under active evaluation. This paper outlines the rationale behind the initiative, introduces Hyperliquid, and explores how such a listing could support the broader growth of LSVs and SubDAOs.

StaFi DAO will publish a report every month to disclose the DAO’s financial status and data.

At StaFi, we’ve been pioneering Liquid Staking as a Service (LSaaS) to bring liquidity to PoS tokens. Today, we want to introduce a brand new idea which is the new infrastructure module designed specifically for non-PoS tokens, dApps, and appchains:

StaFi DAO will publish a report every month to disclose the DAO’s financial status and data.

In our relentless pursuit to redefine Liquid Staking as a Service (LSaaS), StaFi is taking another bold step forward by integrating Sonic SVM LST into our stack, paving the way for StaFi’s presence in the Solana SVM ecosystem. Alongside this, StaFi is deploying Hyperliquid LST in the stack, marking a significant milestone in perpetual trading DEX liquidity enhancement. These advancements are set to position StaFi as a pioneer in cross-chain liquid staking infrastructure, unlocking new waves of value and utility for $FIS holders.

Once a month, StaFi DAO spills the (financial) tea — full transparency, zero secrets.

MCP (Model Context Protocol) is a lightweight, modular protocol that structures and supplies context to AI agents at runtime. It acts as a bridge between large language models (LLMs) and live, domain-specific data sources — such as DeFi protocols, DAO governance logs, on-chain analytics, and external APIs — empowering the model to generate highly relevant, data-grounded responses.