Web3 For Beginners

Sentio and The Graph are both used for on-chain data indexing, but they differ clearly in their core design goals. The Graph indexes on-chain data through subgraphs and mainly serves data querying and aggregation needs. Sentio, by contrast, uses a real time indexing mechanism that emphasizes low latency data processing, visual monitoring, and automated alerting, making it more suitable for real time monitoring and risk warning scenarios.

Sentio’s real-time data indexing mechanism continuously monitors on-chain events, then parses, processes, and outputs data as soon as it is generated, enabling low latency data monitoring. Its real-time data processing flow mainly includes four stages: event monitoring, data parsing, structured processing, and real-time output, supporting DeFi protocol monitoring, security alerts, and on-chain operations analysis. Compared with traditional on-chain data platforms, Sentio places greater emphasis on real-time, event-driven processing, allowing raw blockchain logs to be quickly transformed into visual metrics and automated alert information.

Sentio (ST) is a real-time on-chain data infrastructure designed for the Web3 ecosystem, providing developers and protocols with instant data indexing, visual analytics, and automated alerting capabilities. Compared to traditional on-chain data platforms, Sentio places greater emphasis on real-time responsiveness and monitoring, enabling DeFi protocols, development teams, and analytics use cases to quickly capture blockchain events and generate actionable insights. By integrating real-time indexing, dashboard visualization, and automated alert mechanisms, Sentio delivers a more efficient data infrastructure layer for Web3 applications, playing a key role in areas such as protocol monitoring, risk alerts, and operational analytics.

SkyAI (SKYAI) is a protocol dedicated to merging AI with Web3 data infrastructure. By expanding the MCP (Model Context Protocol), aggregating multi-chain data, and enhancing data liquidity mechanisms, it delivers efficient on-chain data services for AI Agents and decentralized applications. Its primary goal is to convert fragmented on-chain data into accessible and tradable resources, enabling AI models to more effectively interpret and leverage blockchain data. With the rapid growth of AI Agents and on-chain automated applications, SkyAI is emerging as a leading force in the AI + Web3 data infrastructure landscape.

ST is the core utility token of the Sentio ecosystem, acting as the primary medium for value transfer among developers, data infrastructure, and network participants. As a key component of Sentio’s real-time on-chain data network, ST is used for resource utilization, network incentives, and ecosystem collaboration, supporting the platform in building a sustainable data service model. By implementing the ST token mechanism, Sentio combines network resource usage with ecosystem incentives, allowing developers to access real-time data services more efficiently and strengthening the long-term sustainability of the entire data network.

The workflow of cryptocurrency OTC trading typically includes trade initiation, RFQ (Request for Quote), multiple price submissions, price selection, and final settlement. By relying on market makers to provide liquidity, OTC trading reduces slippage and avoids market impact. With the introduction of algorithmic trading, the OTC process is increasingly becoming automated, allowing institutions to execute trades efficiently and consistently across fragmented liquidity environments.

Algorithmic trading, or algo trading, refers to the use of programmed models to automate trading decisions and order execution. In the crypto OTC market, it is primarily used to optimize the RFQ, or request for quote, process and enable smart routing and liquidity aggregation, helping traders achieve best execution in a fragmented market. Through automated quote distribution, real time price analysis, and path optimization, algorithmic trading not only significantly reduces slippage and market impact, but has also become core infrastructure for institutional block trading, driving the OTC market toward greater electronic and systematic development.

In the cryptocurrency market, institutions typically execute large trades by combining RFQ (Request for Quote) with algorithmic trading. RFQ is used to obtain customized quotes from multiple liquidity providers, while algorithmic trading automates request distribution, optimizes quote selection, and ensures best execution. Together, this approach reduces slippage, minimizes market impact, and improves execution efficiency, making it a core method for institutional trading in today’s OTC markets.

RFQ, or Request for Quote, is a pricing mechanism widely used in crypto OTC trading. It allows traders to request quotes from multiple liquidity providers and select the best available price to execute a trade. Compared to traditional order book matching, RFQ helps reduce slippage, minimizes market impact, and supports large transactions. With the rise of algorithmic trading, the RFQ process is becoming increasingly automated and intelligently routed, making it a foundational component of institutional-grade trading infrastructure.

Crypto over the counter trading, or OTC, is a way to execute large transactions outside of public exchanges, typically facilitated by market makers or brokers. At its core is the RFQ, or Request for Quote mechanism, which allows traders to obtain customized pricing and complete large deals while minimizing slippage and market impact. As algorithmic trading continues to evolve, the OTC market is becoming more automated and intelligent, improving both liquidity and execution efficiency. OTC trading is best suited for high net worth individuals, institutions, and those handling large orders, but it also involves liquidity, counterparty, and regulatory risks.

The role of idOS in stablecoin ecosystems lies in providing a reusable on-chain identity infrastructure that allows users to share verified identity data across different financial applications. Through encrypted storage and permissioned access, idOS enables stablecoin platforms to verify user identities without requiring repeated KYC processes, reducing compliance costs while improving user experience. By introducing an identity layer, stablecoins can meet regulatory requirements without compromising privacy, serving as a crucial bridge between on-chain finance and the real world.

The core mechanism of idOS revolves around “encrypted storage plus access authorization (Access Grant).” User identity data is first verified by an issuer and then encrypted and stored within the idOS network. Applications, known as consumers, can only access this data after receiving user authorization. Through this process, idOS enables reusable identity data, protects privacy, and allows secure data portability across applications, making it possible to use sensitive information like KYC across platforms without repeated submissions.

idOS (IDOS) is a Web3 identity layer that provides users with portable identity verification and self-custodied data storage, allowing KYC information to be reused across platforms. By linking identity to blockchain addresses, idOS addresses fragmentation and repetitive verification in Web3, emerging as a critical infrastructure connecting users, applications, and compliance systems within the stablecoin economy.

OPN is the core token within the Opinion Labs ecosystem, designed to coordinate incentives and value distribution across on-chain prediction markets and real-world data systems. Its tokenomics model captures value during the transformation of real-world information into tradable assets by rewarding data providers, prediction participants, and validation nodes. At its core, OPN leverages supply and demand dynamics alongside market-driven incentives to improve data quality, enhance market liquidity, and support the efficient operation of the entire data assetization network.

Opinion uses Oracles and blockchain infrastructure to convert news, macroeconomic data, and event outcomes into verifiable data streams, which are then standardized into tradable market contracts. Its core mechanisms include data collection, validation, on-chain submission, and result settlement, enabling users to predict and trade around real-world events. The key value of this system lies in transforming fragmented and unstructured information into priceable, composable on-chain assets, thereby improving transparency and efficiency in information markets.