PythRoadmap
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Why is Data Directly from the Source More Reliable?
In the world of digital finance, the accuracy of asset price information such as stocks or crypto is everything. However, many platforms we use actually present second-hand data—information that has been collected and reprocessed by other data providers, which can lead to delays or inaccuracies.
A project called Pyth Network comes with a different approach. They build their foundation on what is called first-party data.
So, what is the difference from regular data?
First-party data is raw data that is sent directly from its original source, without intermediaries. Imagine you want to know the latest price of a stock. Instead of asking a friend who heard it from someone else (second-party data), you directly ask the trader on the exchange who just made a transaction.
In the Pyth ecosystem, this price data comes directly from market makers and leading exchanges that are actually trading in the market. They provide their transaction information directly to the Pyth network.
Why is this important?
By cutting out the intermediary chain, the data that reaches the user becomes:
· Fast: Minimal delay.
· Accurate: Directly from market participants.
· Transparent: The data sources are clear and trustworthy.
In essence, first-party data from Pyth aims to provide a more reliable foundation for future financial applications, ensuring that every investment decision is based on trustworthy information directly from the source. #pythroadmap $PYTH @Pyth Network
In the world of digital finance, the accuracy of asset price information such as stocks or crypto is everything. However, many platforms we use actually present second-hand data—information that has been collected and reprocessed by other data providers, which can lead to delays or inaccuracies.
A project called Pyth Network comes with a different approach. They build their foundation on what is called first-party data.
So, what is the difference from regular data?
First-party data is raw data that is sent directly from its original source, without intermediaries. Imagine you want to know the latest price of a stock. Instead of asking a friend who heard it from someone else (second-party data), you directly ask the trader on the exchange who just made a transaction.
In the Pyth ecosystem, this price data comes directly from market makers and leading exchanges that are actually trading in the market. They provide their transaction information directly to the Pyth network.
Why is this important?
By cutting out the intermediary chain, the data that reaches the user becomes:
· Fast: Minimal delay.
· Accurate: Directly from market participants.
· Transparent: The data sources are clear and trustworthy.
In essence, first-party data from Pyth aims to provide a more reliable foundation for future financial applications, ensuring that every investment decision is based on trustworthy information directly from the source. #pythroadmap $PYTH @Pyth Network
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Exciting news from Pyth Network! 🚀 They are not just staying in the DeFi space but are targeting a massive data market worth $50+ billion, aiming to become the leading source of reliable market data. The second phase of their roadmap includes the launch of a subscription product for institutional data, which will significantly increase institutional adoption. The token $PYTH plays a key role, providing incentives for network participants and DAO revenue distribution. The future of decentralized data looks bright! @Pyth Network
#pythroadmap
#pythroadmap
$PYTH Network is the future of oracles!
📊 Real-time prices direct from exchanges & trading firms
🌍 Live on dozens of blockchains
📈 Covering crypto, stocks, forex, ETFs & commodities
🔒 Trusted by DeFi + institutions (even powering US economic data on-chain)
🔥 $PYTH token drives governance & rewards publishers
$PYTH @Pyth Network ##pythroadmap
📊 Real-time prices direct from exchanges & trading firms
🌍 Live on dozens of blockchains
📈 Covering crypto, stocks, forex, ETFs & commodities
🔒 Trusted by DeFi + institutions (even powering US economic data on-chain)
🔥 $PYTH token drives governance & rewards publishers
$PYTH @Pyth Network ##pythroadmap
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🚀 @Pythnetwork is embarking on a new journey with the ambitious #PythRoadmap! The vision is to expand beyond DeFi, targeting the $50 billion market data industry. 🌍 In phase two, Pyth will launch an organizational-grade data subscription product, providing comprehensive and reliable data sources for businesses. $PYTH plays a crucial role in both incentivizing contributors and distributing DAO revenue, creating a sustainable and transparent ecosystem.
#pythroadmap $PYTH
#pythroadmap $PYTH
Article 1: “Binance & Pyth Network: Powering the Future of Real-Time Finance”
In the evolving world of Web3, data is king — and Pyth Network is emerging as a foundational oracle infrastructure bridging real-world markets and blockchain ecosystems. On Binance’s publishing channel, the exchange recently outlined how Pyth’s architecture, scalability, and trust model position it as a next-generation oracle for high-frequency DeFi.
Why Pyth matters
Traditional oracle designs often struggle with latency, data integrity, or centralization. Pyth tackles those by bringing first-party market data providers (trading firms, exchanges) on-chain, aggregating real-time feeds with confidence intervals, and making them available cross-chain.
Binance’s role & listing
Binance officially listed $PYTH in early 2024, granting users access to PYTH/USDT, PYTH/BTC, and other pairs, with a “Seed Tag” to reflect the project’s innovative but still maturing status. Beyond listing, Binance now also integrates Pyth data feeds across BNB Chain and Binance sidechains, enabling BNB native apps to access more than 80 high-fidelity price feeds.
Roadmap & vision
Pyth’s roadmap aims to extend far beyond DeFi price oracles. In its Phase 2, Pyth is exploring institutional monetization: data subscription models, risk analytics, and expanding into the $50B+ traditional market data industry. The vision includes permissionless cross-chain scaling, governance by token holders, and making real-world macro data (e.g. US GDP) available on blockchains.
The synergy
Together, Binance and Pyth aim to push the frontier of decentralized finance. Binance’s reach and infrastructure support gives Pyth broad exposure, while Pyth’s data feeds enrich Binance’s on-chain and off-chain offerings. For crypto enthusiasts, builders, and institutional actors, this collaboration signals a shift: from oracles purely for DeFi, toward a financial data fabric for all d
igital ecosystems.
#pythroadmap $PYTH @Pyth Network
Why Pyth matters
Traditional oracle designs often struggle with latency, data integrity, or centralization. Pyth tackles those by bringing first-party market data providers (trading firms, exchanges) on-chain, aggregating real-time feeds with confidence intervals, and making them available cross-chain.
Binance’s role & listing
Binance officially listed $PYTH in early 2024, granting users access to PYTH/USDT, PYTH/BTC, and other pairs, with a “Seed Tag” to reflect the project’s innovative but still maturing status. Beyond listing, Binance now also integrates Pyth data feeds across BNB Chain and Binance sidechains, enabling BNB native apps to access more than 80 high-fidelity price feeds.
Roadmap & vision
Pyth’s roadmap aims to extend far beyond DeFi price oracles. In its Phase 2, Pyth is exploring institutional monetization: data subscription models, risk analytics, and expanding into the $50B+ traditional market data industry. The vision includes permissionless cross-chain scaling, governance by token holders, and making real-world macro data (e.g. US GDP) available on blockchains.
The synergy
Together, Binance and Pyth aim to push the frontier of decentralized finance. Binance’s reach and infrastructure support gives Pyth broad exposure, while Pyth’s data feeds enrich Binance’s on-chain and off-chain offerings. For crypto enthusiasts, builders, and institutional actors, this collaboration signals a shift: from oracles purely for DeFi, toward a financial data fabric for all d
igital ecosystems.
#pythroadmap $PYTH @Pyth Network
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The low-latency innovations of the Pyth Network's impact on the future of perpetual markets
• Latency Breakthrough: By 2030, the Pyth Lazer update frequency will reach 100 milliseconds, supporting a trillion-dollar trading market for perpetual futures; currently processing $100 billion in daily trading, with future integration of quantum-safe encryption to prevent attacks.
• Cost and Efficiency: Pull-based feeds enable pay-per-use, optimizing costs, with TVL efficiency improved by 60%; PYTH DAO governance updates frequency parameters, and the token burn mechanism stabilizes supply.
• Collaboration and Applications: Collaborating with OKX and Binance to ensure the accuracy of first-party data; eliminating trading slippage, empowering high-frequency trading dApps, and driving the migration of perpetual markets from centralized to decentralized, expected to release $300 billion in liquidity.
@Pyth Network #pythroadmap $PYTH
• Latency Breakthrough: By 2030, the Pyth Lazer update frequency will reach 100 milliseconds, supporting a trillion-dollar trading market for perpetual futures; currently processing $100 billion in daily trading, with future integration of quantum-safe encryption to prevent attacks.
• Cost and Efficiency: Pull-based feeds enable pay-per-use, optimizing costs, with TVL efficiency improved by 60%; PYTH DAO governance updates frequency parameters, and the token burn mechanism stabilizes supply.
• Collaboration and Applications: Collaborating with OKX and Binance to ensure the accuracy of first-party data; eliminating trading slippage, empowering high-frequency trading dApps, and driving the migration of perpetual markets from centralized to decentralized, expected to release $300 billion in liquidity.
@Pyth Network #pythroadmap $PYTH
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2030 Pyth Network's Regulatory Compliance Oracle Standard
• Standard Positioning: To become the global oracle standard by 2030, build a MiCA and CFTC compatible framework, address regulatory uncertainty, and provide compliant real-time data.
• Security and Governance: Oracle Integrity Staking expands from $135 million to $1 billion to incentivize validators; white paper governance will incorporate audit logs into DAO proposals to support cross-jurisdictional data transfer.
• Collaboration and Tokens: Integration with Euroclear and Swift to achieve TradFi on-chain settlement and prevent data manipulation; PYTH used for compliance module rewards, with price potential exceeding $10.
• Industry Value: Standardized data formats for developers to integrate with one click; expected to process 50% of global financial data by 2030, driving the transformation of oracle from experimentation to infrastructure.
@Pyth Network #pythroadmap $PYTH
• Standard Positioning: To become the global oracle standard by 2030, build a MiCA and CFTC compatible framework, address regulatory uncertainty, and provide compliant real-time data.
• Security and Governance: Oracle Integrity Staking expands from $135 million to $1 billion to incentivize validators; white paper governance will incorporate audit logs into DAO proposals to support cross-jurisdictional data transfer.
• Collaboration and Tokens: Integration with Euroclear and Swift to achieve TradFi on-chain settlement and prevent data manipulation; PYTH used for compliance module rewards, with price potential exceeding $10.
• Industry Value: Standardized data formats for developers to integrate with one click; expected to process 50% of global financial data by 2030, driving the transformation of oracle from experimentation to infrastructure.
@Pyth Network #pythroadmap $PYTH
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Pyth's brand new Roadmap is out, targeting the institutional market worth 50 billion USD
1️⃣ Phase One: Laying the Foundation —— Leading DeFi, creating valuable data sources ✅ (Completed)
2️⃣ Phase Two: Unlocking the 50 billion USD institutional market 🔥 (In Progress)
👉 The biggest highlight is that the revenue model may directly link to $PYTH , and rumors do not rule out the possibility of a buyback logic
3️⃣ Phase Three: Becoming the Price Layer of the global market 🌍 (Next Goal)
In summary:
In DeFi, Pyth has already proven itself; whether it will truly enter TradFi with real money depends on the wallets of institutions and the value capture mechanism of $PYTH .22
@Pyth Network #pythroadmap $PYTH
1️⃣ Phase One: Laying the Foundation —— Leading DeFi, creating valuable data sources ✅ (Completed)
2️⃣ Phase Two: Unlocking the 50 billion USD institutional market 🔥 (In Progress)
👉 The biggest highlight is that the revenue model may directly link to $PYTH , and rumors do not rule out the possibility of a buyback logic
3️⃣ Phase Three: Becoming the Price Layer of the global market 🌍 (Next Goal)
In summary:
In DeFi, Pyth has already proven itself; whether it will truly enter TradFi with real money depends on the wallets of institutions and the value capture mechanism of $PYTH .22
@Pyth Network #pythroadmap $PYTH
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The overall future of Pyth Network: A global financial data revolution
• Ultimate vision: Revolutionizing global financial data by 2030, providing end-to-end real-time oracles, supporting trillion-dollar applications; currently 437+ dApp integrations, with future integration of AI and DePIN to achieve predictive feeds.
• Governance and value: PYTH promotes democratic decision-making, with price potential exceeding $20; collaborating with government partners to bridge traditional finance and unlock locked value.
• Industry transformation: Driving the transition of financial data from centralized monopolies to decentralized sharing, empowering 1 billion users as infrastructure.
@Pyth Network #pythroadmap $PYTH
• Ultimate vision: Revolutionizing global financial data by 2030, providing end-to-end real-time oracles, supporting trillion-dollar applications; currently 437+ dApp integrations, with future integration of AI and DePIN to achieve predictive feeds.
• Governance and value: PYTH promotes democratic decision-making, with price potential exceeding $20; collaborating with government partners to bridge traditional finance and unlock locked value.
• Industry transformation: Driving the transition of financial data from centralized monopolies to decentralized sharing, empowering 1 billion users as infrastructure.
@Pyth Network #pythroadmap $PYTH
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Pyth Network and the 2030 Integration with Multiple Oracle Ecosystems
• Integration Model: In 2030, integrate with Chainlink and other oracles to form a multi-source data layer, providing redundant real-time feeds to enhance reliability; achieve seamless integration through atomic swaps, with aggregation algorithms superior to singular sources.
• Governance and Market: DAO coordinates cross-oracle data standards, PYTH tokens support cross-network circulation; expected to occupy 40% market share, processing global financial data streams.
• Security and Innovation: Multi-layer verification prevents single points of failure, giving rise to hybrid functional dApps, driving the transformation of oracles from competition to collaboration.
@Pyth Network #pythroadmap $PYTH
• Integration Model: In 2030, integrate with Chainlink and other oracles to form a multi-source data layer, providing redundant real-time feeds to enhance reliability; achieve seamless integration through atomic swaps, with aggregation algorithms superior to singular sources.
• Governance and Market: DAO coordinates cross-oracle data standards, PYTH tokens support cross-network circulation; expected to occupy 40% market share, processing global financial data streams.
• Security and Innovation: Multi-layer verification prevents single points of failure, giving rise to hybrid functional dApps, driving the transformation of oracles from competition to collaboration.
@Pyth Network #pythroadmap $PYTH
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Pyth Network: The Ambition from DeFi to Institutional-Level Data Market!
The vision of Pyth Network goes far beyond the DeFi space! Their roadmap's second phase is exciting, aiming to expand into the traditional market data industry worth over $50 billion, focusing on creating a trusted comprehensive data source for institutions. This means Pyth is evolving from a price feed tool to an institutional-level data subscription product, which is the true point of value explosion.
This institutional-level application has extremely high requirements for data accuracy and low latency, and Pyth, with its unique data source aggregation mechanism, fits perfectly. In addition, $PYTH tokens not only incentivize ecosystem contributors but also ensure the reasonable distribution of DAO revenue, which is key to the decentralization and long-term sustainability of the entire network.
Which type of traditional data service provider do you think Pyth is most likely to replace after expanding into the traditional financial market?
#pythroadmap $PYTH @Pyth Network
The vision of Pyth Network goes far beyond the DeFi space! Their roadmap's second phase is exciting, aiming to expand into the traditional market data industry worth over $50 billion, focusing on creating a trusted comprehensive data source for institutions. This means Pyth is evolving from a price feed tool to an institutional-level data subscription product, which is the true point of value explosion.
This institutional-level application has extremely high requirements for data accuracy and low latency, and Pyth, with its unique data source aggregation mechanism, fits perfectly. In addition, $PYTH tokens not only incentivize ecosystem contributors but also ensure the reasonable distribution of DAO revenue, which is key to the decentralization and long-term sustainability of the entire network.
Which type of traditional data service provider do you think Pyth is most likely to replace after expanding into the traditional financial market?
#pythroadmap $PYTH @Pyth Network
𝗟𝗼𝘄-𝗟𝗮𝘁𝗲𝗻𝗰𝘆, 𝗙𝗶𝗿𝘀𝘁-𝗣𝗮𝗿𝘁𝘆 𝗗𝗮𝘁𝗮 𝗙𝗲𝗲𝗱𝘀:
𝗣𝘆𝘁𝗵'𝘀 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗮𝗹 𝗘𝗻𝗮𝗯𝗹𝗲𝗺𝗲𝗻𝘁 𝗼𝗳 𝗗𝗲𝗰𝗲𝗻𝘁𝗿𝗮𝗹𝗶𝘇𝗲𝗱 𝗗𝗲𝗿𝗶𝘃𝗮𝘁𝗶𝘃𝗲𝘀
The emergence of 𝗱𝗲𝗰𝗲𝗻𝘁𝗿𝗮𝗹𝗶𝘇𝗲𝗱 𝗱𝗲𝗿𝗶𝘃𝗮𝘁𝗶𝘃𝗲𝘀, such as 𝗽𝗲𝗿𝗽𝗲𝘁𝘂𝗮𝗹 𝘀𝘄𝗮𝗽𝘀 and 𝗼𝗽𝘁𝗶𝗼𝗻𝘀, marks a significant maturation point for 𝗗𝗲𝗰𝗲𝗻𝘁𝗿𝗮𝗹𝗶𝘇𝗲𝗱 𝗙𝗶𝗻𝗮𝗻𝗰𝗲 (𝗗𝗲𝗙𝗶). However, these complex financial instruments necessitate real-time 𝗱𝗮𝘁𝗮 𝗳𝗶𝗱𝗲𝗹𝗶𝘁𝘆 and 𝘁𝗿𝗮𝗻𝘀𝗮𝗰𝘁𝗶𝗼𝗻𝗮𝗹 𝘀𝗽𝗲𝗲𝗱 traditionally confined to 𝗧𝗿𝗮𝗱𝗙𝗶 infrastructure. The 𝗣𝘆𝘁𝗵 𝗡𝗲𝘁𝘄𝗼𝗿𝗸 acts as a high-performance 𝗼𝗿𝗮𝗰𝗹𝗲 𝗹𝗮𝘆𝗲𝗿, enabling the security, efficiency, and scalability of 𝗼𝗻-𝗰𝗵𝗮𝗶𝗻 𝗱𝗲𝗿𝗶𝘃𝗮𝘁𝗶𝘃𝗲𝘀.
𝗧𝗵𝗲 𝗖𝗼𝗿𝗲 𝗣𝗿𝗼𝗯𝗹𝗲𝗺: 𝗟𝗮𝘁𝗲𝗻𝗰𝘆 𝗮𝗻𝗱 𝗗𝗮𝘁𝗮 𝗜𝗻𝘁𝗲𝗴𝗿𝗶𝘁𝘆
𝗗𝗲𝗰𝗲𝗻𝘁𝗿𝗮𝗹𝗶𝘇𝗲𝗱 𝗱𝗲𝗿𝗶𝘃𝗮𝘁𝗶𝘃𝗲𝘀 𝗽𝗿𝗼𝘁𝗼𝗰𝗼𝗹𝘀—especially 𝗺𝗮𝗿𝗴𝗶𝗻 𝘁𝗿𝗮𝗱𝗶𝗻𝗴 and 𝗽𝗲𝗿𝗽𝗲𝘁𝘂𝗮𝗹 𝗳𝘂𝘁𝘂𝗿𝗲𝘀—are highly sensitive to two factors:
𝗟𝗶𝗾𝘂𝗶𝗱𝗮𝘁𝗶𝗼𝗻 𝗘𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝗰𝘆 (𝗟𝗮𝘁𝗲𝗻𝗰𝘆): Large market swings demand near-instant 𝗽𝗿𝗶𝗰𝗲 𝘂𝗽𝗱𝗮𝘁𝗲𝘀 to avoid 𝗶𝗻𝘀𝗼𝗹𝘃𝗲𝗻𝗰𝘆 or 𝗯𝗮𝗱 𝗱𝗲𝗯𝘁.
𝗙𝗿𝗼𝗻𝘁-𝗥𝘂𝗻𝗻𝗶𝗻𝗴 𝗮𝗻𝗱 𝗠𝗮𝗻𝗶𝗽𝘂𝗹𝗮𝘁𝗶𝗼𝗻 (𝗜𝗻𝘁𝗲𝗴𝗿𝗶𝘁𝘆): Predictable or slow oracles allow 𝘀𝗼𝗽𝗵𝗶𝘀𝘁𝗶𝗰𝗮𝘁𝗲𝗱 𝘁𝗿𝗮𝗱𝗲𝗿𝘀 to exploit delays, causing manipulation risks.
𝗣𝘆𝘁𝗵'𝘀 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 directly mitigates these challenges.
𝗣𝘆𝘁𝗵'𝘀 𝗧𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 𝗣𝗶𝗹𝗹𝗮𝗿𝘀 𝗳𝗼𝗿 𝗗𝗲𝗿𝗶𝘃𝗮𝘁𝗶𝘃𝗲𝘀
1. 𝗙𝗶𝗿𝘀𝘁-𝗣𝗮𝗿𝘁𝘆 𝗗𝗮𝘁𝗮 𝗦𝗼𝘂𝗿𝗰𝗶𝗻𝗴 𝗮𝗻𝗱 𝗔𝗴𝗴𝗿𝗲𝗴𝗮𝘁𝗶𝗼𝗻
𝗛𝗶𝗴𝗵-𝗙𝗶𝗱𝗲𝗹𝗶𝘁𝘆 𝗜𝗻𝗽𝘂𝘁: Over 𝟭𝟮𝟬 𝗶𝗻𝘀𝘁𝗶𝘁𝘂𝘁𝗶𝗼𝗻𝗮𝗹 𝗽𝘂𝗯𝗹𝗶𝘀𝗵𝗲𝗿𝘀 (exchanges, market makers, financial institutions) provide 𝗿𝗲𝗮𝗹-𝘁𝗶𝗺𝗲 𝗾𝘂𝗼𝘁𝗲𝘀.
𝗖𝗼𝗻𝗳𝗶𝗱𝗲𝗻𝗰𝗲 𝗜𝗻𝘁𝗲𝗿𝘃𝗮𝗹 (𝗖𝗜): Aggregation on 𝗣𝘆𝘁𝗵𝗻𝗲𝘁 produces 𝗔𝗴𝗴𝗿𝗲𝗴𝗮𝘁𝗲 𝗣𝗿𝗶𝗰𝗲 ± 𝗖𝗜.
Narrow 𝗖𝗜 = strong market consensus.
Wide 𝗖𝗜 = higher risk, adjustable liquidation thresholds.
2. 𝗧𝗵𝗲 𝗣𝘂𝗹𝗹 𝗢𝗿𝗮𝗰𝗹𝗲 𝗠𝗼𝗱𝗲𝗹 (𝗢𝗻-𝗗𝗲𝗺𝗮𝗻𝗱 𝗨𝗽𝗱𝗮𝘁𝗲𝘀)
𝗧𝗿𝗮𝗱𝗶𝘁𝗶𝗼𝗻𝗮𝗹 (𝗣𝘂𝘀𝗵) 𝗠𝗼𝗱𝗲𝗹: Constant data pushing = high 𝗴𝗮𝘀 𝗰𝗼𝘀𝘁𝘀 + limited frequency.
𝗣𝘆𝘁𝗵 (𝗣𝘂𝗹𝗹) 𝗠𝗼𝗱𝗲𝗹:
Updates stored 𝗼𝗳𝗳-𝗰𝗵𝗮𝗶𝗻.
When needed (e.g., 𝘁𝗿𝗮𝗱𝗲, 𝗹𝗶𝗾𝘂𝗶𝗱𝗮𝘁𝗶𝗼𝗻), 𝗰𝗿𝘆𝗽𝘁𝗼𝗴𝗿𝗮𝗽𝗵𝗶𝗰𝗮𝗹𝗹𝘆 𝘀𝗶𝗴𝗻𝗲𝗱 𝗽𝗿𝗶𝗰𝗲 is pulled on-chain.
✅ Enables 𝘀𝘂𝗯-𝘀𝗲𝗰𝗼𝗻𝗱, 𝗼𝗻-𝗱𝗲𝗺𝗮𝗻𝗱 𝘂𝗽𝗱𝗮𝘁𝗲𝘀 at execution time.
3. 𝗠𝘂𝗹𝘁𝗶-𝗖𝗵𝗮𝗶𝗻 𝗗𝗶𝘀𝘁𝗿𝗶𝗯𝘂𝘁𝗶𝗼𝗻 𝘃𝗶𝗮 𝗪𝗼𝗿𝗺𝗵𝗼𝗹𝗲
Broadcasts aggregated price feeds to 𝟭𝟬𝟬+ 𝗯𝗹𝗼𝗰𝗸𝗰𝗵𝗮𝗶𝗻𝘀.
Ensures 𝗲𝘅𝗮𝗰𝘁 𝘀𝗮𝗺𝗲 𝗱𝗮𝘁𝗮 across ecosystems (Ethereum, Solana, Arbitrum, Optimism, etc.).
Reduces 𝗰𝗿𝗼𝘀𝘀-𝗰𝗵𝗮𝗶𝗻 𝗮𝗿𝗯𝗶𝘁𝗿𝗮𝗴𝗲 risks, improves 𝗰𝗮𝗽𝗶𝘁𝗮𝗹 𝗲𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝗰𝘆.
𝗜𝗺𝗽𝗮𝗰𝘁 𝗼𝗻 𝗗𝗲𝗰𝗲𝗻𝘁𝗿𝗮𝗹𝗶𝘇𝗲𝗱 𝗗𝗲𝗿𝗶𝘃𝗮𝘁𝗶𝘃𝗲𝘀 𝗣𝗿𝗼𝘁𝗼𝗰𝗼𝗹𝘀
𝗙𝗲𝗮𝘁𝘂𝗿𝗲 𝗣𝘆𝘁𝗵'𝘀 𝗧𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 𝗥𝗼𝗹𝗲 𝗕𝗲𝗻𝗲𝗳𝗶𝘁 𝘁𝗼 𝗗𝗲𝗿𝗶𝘃𝗮𝘁𝗶𝘃𝗲𝘀 𝗣𝗿𝗼𝘁𝗼𝗰𝗼𝗹𝘀
𝗟𝗶𝗾𝘂𝗶𝗱𝗮𝘁𝗶𝗼𝗻 𝗦𝗽𝗲𝗲𝗱 𝗣𝘂𝗹𝗹 𝗠𝗼𝗱𝗲𝗹 enables sub-second updates Prevents 𝗯𝗮𝗱 𝗱𝗲𝗯𝘁 + ensures 𝗽𝗿𝗼𝘁𝗼𝗰𝗼𝗹 𝘀𝗼𝗹𝘃𝗲𝗻𝗰𝘆
𝗗𝗮𝘁𝗮 𝗜𝗻𝘁𝗲𝗴𝗿𝗶𝘁𝘆 𝗙𝗶𝗿𝘀𝘁-𝗣𝗮𝗿𝘁𝘆 𝗦𝗼𝘂𝗿𝗰𝗶𝗻𝗴 + 𝗖𝗼𝗻𝗳𝗶𝗱𝗲𝗻𝗰𝗲 𝗜𝗻𝘁𝗲𝗿𝘃𝗮𝗹 Defends against 𝗺𝗮𝗻𝗶𝗽𝘂𝗹𝗮𝘁𝗶𝗼𝗻 + 𝗳𝗹𝗮𝘀𝗵 𝗹𝗼𝗮𝗻 𝗮𝘁𝘁𝗮𝗰𝗸𝘀
𝗙𝘂𝗻𝗱𝗶𝗻𝗴 𝗥𝗮𝘁𝗲𝘀 ~400𝗺𝘀 𝗽𝗿𝗶𝗰𝗲 𝘂𝗽𝗱𝗮𝘁𝗲𝘀 Keeps 𝗽𝗲𝗿𝗽𝗲𝘁𝘂𝗮𝗹 𝗰𝗼𝗻𝘁𝗿𝗮𝗰𝘁𝘀 tightly pegged
𝗦𝗰𝗮𝗹𝗮𝗯𝗶𝗹𝗶𝘁𝘆 𝗣𝘂𝗹𝗹 𝗠𝗼𝗱𝗲𝗹 cuts 𝗴𝗮𝘀 𝗰𝗼𝘀𝘁𝘀 Enables growth without prohibitive 𝗼𝗿𝗮𝗰𝗹𝗲 𝗰𝗼𝘀𝘁𝘀
#pythroadmap
@Pyth Network
$PYTH
The emergence of 𝗱𝗲𝗰𝗲𝗻𝘁𝗿𝗮𝗹𝗶𝘇𝗲𝗱 𝗱𝗲𝗿𝗶𝘃𝗮𝘁𝗶𝘃𝗲𝘀, such as 𝗽𝗲𝗿𝗽𝗲𝘁𝘂𝗮𝗹 𝘀𝘄𝗮𝗽𝘀 and 𝗼𝗽𝘁𝗶𝗼𝗻𝘀, marks a significant maturation point for 𝗗𝗲𝗰𝗲𝗻𝘁𝗿𝗮𝗹𝗶𝘇𝗲𝗱 𝗙𝗶𝗻𝗮𝗻𝗰𝗲 (𝗗𝗲𝗙𝗶). However, these complex financial instruments necessitate real-time 𝗱𝗮𝘁𝗮 𝗳𝗶𝗱𝗲𝗹𝗶𝘁𝘆 and 𝘁𝗿𝗮𝗻𝘀𝗮𝗰𝘁𝗶𝗼𝗻𝗮𝗹 𝘀𝗽𝗲𝗲𝗱 traditionally confined to 𝗧𝗿𝗮𝗱𝗙𝗶 infrastructure. The 𝗣𝘆𝘁𝗵 𝗡𝗲𝘁𝘄𝗼𝗿𝗸 acts as a high-performance 𝗼𝗿𝗮𝗰𝗹𝗲 𝗹𝗮𝘆𝗲𝗿, enabling the security, efficiency, and scalability of 𝗼𝗻-𝗰𝗵𝗮𝗶𝗻 𝗱𝗲𝗿𝗶𝘃𝗮𝘁𝗶𝘃𝗲𝘀.
𝗧𝗵𝗲 𝗖𝗼𝗿𝗲 𝗣𝗿𝗼𝗯𝗹𝗲𝗺: 𝗟𝗮𝘁𝗲𝗻𝗰𝘆 𝗮𝗻𝗱 𝗗𝗮𝘁𝗮 𝗜𝗻𝘁𝗲𝗴𝗿𝗶𝘁𝘆
𝗗𝗲𝗰𝗲𝗻𝘁𝗿𝗮𝗹𝗶𝘇𝗲𝗱 𝗱𝗲𝗿𝗶𝘃𝗮𝘁𝗶𝘃𝗲𝘀 𝗽𝗿𝗼𝘁𝗼𝗰𝗼𝗹𝘀—especially 𝗺𝗮𝗿𝗴𝗶𝗻 𝘁𝗿𝗮𝗱𝗶𝗻𝗴 and 𝗽𝗲𝗿𝗽𝗲𝘁𝘂𝗮𝗹 𝗳𝘂𝘁𝘂𝗿𝗲𝘀—are highly sensitive to two factors:
𝗟𝗶𝗾𝘂𝗶𝗱𝗮𝘁𝗶𝗼𝗻 𝗘𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝗰𝘆 (𝗟𝗮𝘁𝗲𝗻𝗰𝘆): Large market swings demand near-instant 𝗽𝗿𝗶𝗰𝗲 𝘂𝗽𝗱𝗮𝘁𝗲𝘀 to avoid 𝗶𝗻𝘀𝗼𝗹𝘃𝗲𝗻𝗰𝘆 or 𝗯𝗮𝗱 𝗱𝗲𝗯𝘁.
𝗙𝗿𝗼𝗻𝘁-𝗥𝘂𝗻𝗻𝗶𝗻𝗴 𝗮𝗻𝗱 𝗠𝗮𝗻𝗶𝗽𝘂𝗹𝗮𝘁𝗶𝗼𝗻 (𝗜𝗻𝘁𝗲𝗴𝗿𝗶𝘁𝘆): Predictable or slow oracles allow 𝘀𝗼𝗽𝗵𝗶𝘀𝘁𝗶𝗰𝗮𝘁𝗲𝗱 𝘁𝗿𝗮𝗱𝗲𝗿𝘀 to exploit delays, causing manipulation risks.
𝗣𝘆𝘁𝗵'𝘀 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 directly mitigates these challenges.
𝗣𝘆𝘁𝗵'𝘀 𝗧𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 𝗣𝗶𝗹𝗹𝗮𝗿𝘀 𝗳𝗼𝗿 𝗗𝗲𝗿𝗶𝘃𝗮𝘁𝗶𝘃𝗲𝘀
1. 𝗙𝗶𝗿𝘀𝘁-𝗣𝗮𝗿𝘁𝘆 𝗗𝗮𝘁𝗮 𝗦𝗼𝘂𝗿𝗰𝗶𝗻𝗴 𝗮𝗻𝗱 𝗔𝗴𝗴𝗿𝗲𝗴𝗮𝘁𝗶𝗼𝗻
𝗛𝗶𝗴𝗵-𝗙𝗶𝗱𝗲𝗹𝗶𝘁𝘆 𝗜𝗻𝗽𝘂𝘁: Over 𝟭𝟮𝟬 𝗶𝗻𝘀𝘁𝗶𝘁𝘂𝘁𝗶𝗼𝗻𝗮𝗹 𝗽𝘂𝗯𝗹𝗶𝘀𝗵𝗲𝗿𝘀 (exchanges, market makers, financial institutions) provide 𝗿𝗲𝗮𝗹-𝘁𝗶𝗺𝗲 𝗾𝘂𝗼𝘁𝗲𝘀.
𝗖𝗼𝗻𝗳𝗶𝗱𝗲𝗻𝗰𝗲 𝗜𝗻𝘁𝗲𝗿𝘃𝗮𝗹 (𝗖𝗜): Aggregation on 𝗣𝘆𝘁𝗵𝗻𝗲𝘁 produces 𝗔𝗴𝗴𝗿𝗲𝗴𝗮𝘁𝗲 𝗣𝗿𝗶𝗰𝗲 ± 𝗖𝗜.
Narrow 𝗖𝗜 = strong market consensus.
Wide 𝗖𝗜 = higher risk, adjustable liquidation thresholds.
2. 𝗧𝗵𝗲 𝗣𝘂𝗹𝗹 𝗢𝗿𝗮𝗰𝗹𝗲 𝗠𝗼𝗱𝗲𝗹 (𝗢𝗻-𝗗𝗲𝗺𝗮𝗻𝗱 𝗨𝗽𝗱𝗮𝘁𝗲𝘀)
𝗧𝗿𝗮𝗱𝗶𝘁𝗶𝗼𝗻𝗮𝗹 (𝗣𝘂𝘀𝗵) 𝗠𝗼𝗱𝗲𝗹: Constant data pushing = high 𝗴𝗮𝘀 𝗰𝗼𝘀𝘁𝘀 + limited frequency.
𝗣𝘆𝘁𝗵 (𝗣𝘂𝗹𝗹) 𝗠𝗼𝗱𝗲𝗹:
Updates stored 𝗼𝗳𝗳-𝗰𝗵𝗮𝗶𝗻.
When needed (e.g., 𝘁𝗿𝗮𝗱𝗲, 𝗹𝗶𝗾𝘂𝗶𝗱𝗮𝘁𝗶𝗼𝗻), 𝗰𝗿𝘆𝗽𝘁𝗼𝗴𝗿𝗮𝗽𝗵𝗶𝗰𝗮𝗹𝗹𝘆 𝘀𝗶𝗴𝗻𝗲𝗱 𝗽𝗿𝗶𝗰𝗲 is pulled on-chain.
✅ Enables 𝘀𝘂𝗯-𝘀𝗲𝗰𝗼𝗻𝗱, 𝗼𝗻-𝗱𝗲𝗺𝗮𝗻𝗱 𝘂𝗽𝗱𝗮𝘁𝗲𝘀 at execution time.
3. 𝗠𝘂𝗹𝘁𝗶-𝗖𝗵𝗮𝗶𝗻 𝗗𝗶𝘀𝘁𝗿𝗶𝗯𝘂𝘁𝗶𝗼𝗻 𝘃𝗶𝗮 𝗪𝗼𝗿𝗺𝗵𝗼𝗹𝗲
Broadcasts aggregated price feeds to 𝟭𝟬𝟬+ 𝗯𝗹𝗼𝗰𝗸𝗰𝗵𝗮𝗶𝗻𝘀.
Ensures 𝗲𝘅𝗮𝗰𝘁 𝘀𝗮𝗺𝗲 𝗱𝗮𝘁𝗮 across ecosystems (Ethereum, Solana, Arbitrum, Optimism, etc.).
Reduces 𝗰𝗿𝗼𝘀𝘀-𝗰𝗵𝗮𝗶𝗻 𝗮𝗿𝗯𝗶𝘁𝗿𝗮𝗴𝗲 risks, improves 𝗰𝗮𝗽𝗶𝘁𝗮𝗹 𝗲𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝗰𝘆.
𝗜𝗺𝗽𝗮𝗰𝘁 𝗼𝗻 𝗗𝗲𝗰𝗲𝗻𝘁𝗿𝗮𝗹𝗶𝘇𝗲𝗱 𝗗𝗲𝗿𝗶𝘃𝗮𝘁𝗶𝘃𝗲𝘀 𝗣𝗿𝗼𝘁𝗼𝗰𝗼𝗹𝘀
𝗙𝗲𝗮𝘁𝘂𝗿𝗲 𝗣𝘆𝘁𝗵'𝘀 𝗧𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 𝗥𝗼𝗹𝗲 𝗕𝗲𝗻𝗲𝗳𝗶𝘁 𝘁𝗼 𝗗𝗲𝗿𝗶𝘃𝗮𝘁𝗶𝘃𝗲𝘀 𝗣𝗿𝗼𝘁𝗼𝗰𝗼𝗹𝘀
𝗟𝗶𝗾𝘂𝗶𝗱𝗮𝘁𝗶𝗼𝗻 𝗦𝗽𝗲𝗲𝗱 𝗣𝘂𝗹𝗹 𝗠𝗼𝗱𝗲𝗹 enables sub-second updates Prevents 𝗯𝗮𝗱 𝗱𝗲𝗯𝘁 + ensures 𝗽𝗿𝗼𝘁𝗼𝗰𝗼𝗹 𝘀𝗼𝗹𝘃𝗲𝗻𝗰𝘆
𝗗𝗮𝘁𝗮 𝗜𝗻𝘁𝗲𝗴𝗿𝗶𝘁𝘆 𝗙𝗶𝗿𝘀𝘁-𝗣𝗮𝗿𝘁𝘆 𝗦𝗼𝘂𝗿𝗰𝗶𝗻𝗴 + 𝗖𝗼𝗻𝗳𝗶𝗱𝗲𝗻𝗰𝗲 𝗜𝗻𝘁𝗲𝗿𝘃𝗮𝗹 Defends against 𝗺𝗮𝗻𝗶𝗽𝘂𝗹𝗮𝘁𝗶𝗼𝗻 + 𝗳𝗹𝗮𝘀𝗵 𝗹𝗼𝗮𝗻 𝗮𝘁𝘁𝗮𝗰𝗸𝘀
𝗙𝘂𝗻𝗱𝗶𝗻𝗴 𝗥𝗮𝘁𝗲𝘀 ~400𝗺𝘀 𝗽𝗿𝗶𝗰𝗲 𝘂𝗽𝗱𝗮𝘁𝗲𝘀 Keeps 𝗽𝗲𝗿𝗽𝗲𝘁𝘂𝗮𝗹 𝗰𝗼𝗻𝘁𝗿𝗮𝗰𝘁𝘀 tightly pegged
𝗦𝗰𝗮𝗹𝗮𝗯𝗶𝗹𝗶𝘁𝘆 𝗣𝘂𝗹𝗹 𝗠𝗼𝗱𝗲𝗹 cuts 𝗴𝗮𝘀 𝗰𝗼𝘀𝘁𝘀 Enables growth without prohibitive 𝗼𝗿𝗮𝗰𝗹𝗲 𝗰𝗼𝘀𝘁𝘀
#pythroadmap
@Pyth Network
$PYTH
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In the wave of digitalization in the DeFi world and even in traditional finance, there is one crucial question that is often overlooked: how can we reliably obtain real-world data, especially high-speed and high-precision financial market data? The answer to this question determines the reliability and ceiling of the entire on-chain financial system. Pyth Network was created to provide an ultimate answer—it is not an ordinary digital currency, but a first-party decentralized oracle network designed specifically for the next generation of financial applications.
Before Pyth appeared, on-chain applications (such as DeFi protocols and derivatives platforms) mainly relied on traditional oracle solutions. Most of these solutions depended on a few nodes to obtain data from public APIs and aggregate it on-chain. @Pyth Network #pythroadmap $PYTH
Before Pyth appeared, on-chain applications (such as DeFi protocols and derivatives platforms) mainly relied on traditional oracle solutions. Most of these solutions depended on a few nodes to obtain data from public APIs and aggregate it on-chain. @Pyth Network #pythroadmap $PYTH
See original
Pyth's brand new Roadmap is out, aiming for a $50 billion institutional market
1️⃣ Phase One: Laying the Foundation — Leading DeFi, creating valuable data sources ✅ (Completed)
2️⃣ Phase Two: Unlocking the $50 billion institutional market 🔥 (In Progress)
👉 The biggest highlight is that the revenue model may be directly linked to $PYTH , rumors suggest there may be a buyback logic
3️⃣ Phase Three: Becoming the Price Layer for the global market 🌍 (Next Objective)
In summary:
In DeFi, Pyth has already proven itself; the next step is whether to really invest in TradFi with real money, which still depends on the institutional wallet and the value capture mechanism of $PYTH .21
@Pyth Network #pythroadmap $PYTH
1️⃣ Phase One: Laying the Foundation — Leading DeFi, creating valuable data sources ✅ (Completed)
2️⃣ Phase Two: Unlocking the $50 billion institutional market 🔥 (In Progress)
👉 The biggest highlight is that the revenue model may be directly linked to $PYTH , rumors suggest there may be a buyback logic
3️⃣ Phase Three: Becoming the Price Layer for the global market 🌍 (Next Objective)
In summary:
In DeFi, Pyth has already proven itself; the next step is whether to really invest in TradFi with real money, which still depends on the institutional wallet and the value capture mechanism of $PYTH .21
@Pyth Network #pythroadmap $PYTH
Article 1: Binance Embraces PythNetwork’s Vision — A New Era for Market Data
In a bold stride forward, Binance is spotlighting Pyth Network as it charts its next steps along the #PythRoadmap. Through the partnership, Binance aims to turbocharge on-chain access to real-world financial data, leveraging $PYTH as a linchpin in the evolving data economy.
The strategic alignment
Pyth Network was born to bring high-fidelity market data directly to blockchains, bypassing legacy oracle constraints. Binance, in turn, is recognizing the strength of Pyth’s architecture by integrating it across the Binance ecosystem. Whether through its smart chain, sidechains, or data infrastructure, Binance is paving more pathways for dApps to fetch timely, accurate price feeds.
What the #PythRoadmap holds
Phase 1 of Pyth’s roadmap focused heavily on DeFi adoption and cross-chain oracles. But now, as Pyth moves into Phase 2, its vision expands: subscription-level products for institutions, tighter integration with traditional finance, and refined token utility. As noted on Binance Square, Pyth plans to deliver institutional data feeds under clear pricing tiers.
Why this matters
For Binance users, this means richer capabilities in DeFi — more reliable oracle inputs, faster data updates, and seamless integration within BNB Chain apps. For Pyth’s community, it’s a signal of real commitment from a major exchange to support the protocol’s growth. And for $PYTH holders, enhanced usage and broader institutional adoption promise stronger utility and relevance.
The marriage of Binance’s infrastructure muscle and Pyth’s data prowess could very well accelerate the shift toward truly global, real-time finance on-chain — and Binance is already in the vanguard of that movement.
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Article 2: How Binance & Pyth Network Can Power the Future of Finance
As blockchain ecosystems mature, the demand for dependable, real-world financial data becomes ever more critical. That’s where Pyth Network (and its native token $PYTH ) steps in — and Binance is stepping up to amplify its impact.
Pyth’s infrastructure & Binance’s role
Pyth aggregates raw price inputs from leading exchanges, trading firms, and financial institutions, then publishes these feeds on-chain across many blockchain networks. Binance already contributes as one of Pyth’s data providers, reinforcing the credibility of the network. Furthermore, Pyth has launched oracles on BNB Chain and Binance Sidechains, enabling any BNB-native app to access 80+ high-fidelity feeds.
Expanding the #PythRoadmap
In its next roadmap phases, Pyth is pushing beyond DeFi into institutional terrains. The launch of Pyth Pro promises subscription access to cross-asset data for traditional firms, with transparent pricing and broad scope (crypto, equities, FX, commodities). Add to that government and agency collaborations — like with the U.S. Department of Commerce — delivering official economic data on-chain, further cementing Pyth’s status as a trusted oracle.
Benefits & implications
For Binance ecosystem: stronger data infrastructure supports derivatives, lending, prediction markets, and more on BNB Chain apps.
For developers & dApps: they can pull precise, low-latency price feeds with confidence, reducing reliance on external or less secure oracles.
For $PYTH holders: increasing real-world usage, staking possibilities, and governance influence may enhance the token’s long-term value.
By weaving Pyth’s oracle capabilities into its fabric, Binance is not just adopting an oracle — it’s building the scaffolding of tomorrow’s finance. With each milestone on the #PythRoadmap, the union of Binance + Pyth edges us closer to a future where on-chain finance mirrors the complexity and depth of traditional systems — but with transparency,
composability, and accessibility baked in.
#pythroadmap $PYTH @Pyth Network
The strategic alignment
Pyth Network was born to bring high-fidelity market data directly to blockchains, bypassing legacy oracle constraints. Binance, in turn, is recognizing the strength of Pyth’s architecture by integrating it across the Binance ecosystem. Whether through its smart chain, sidechains, or data infrastructure, Binance is paving more pathways for dApps to fetch timely, accurate price feeds.
What the #PythRoadmap holds
Phase 1 of Pyth’s roadmap focused heavily on DeFi adoption and cross-chain oracles. But now, as Pyth moves into Phase 2, its vision expands: subscription-level products for institutions, tighter integration with traditional finance, and refined token utility. As noted on Binance Square, Pyth plans to deliver institutional data feeds under clear pricing tiers.
Why this matters
For Binance users, this means richer capabilities in DeFi — more reliable oracle inputs, faster data updates, and seamless integration within BNB Chain apps. For Pyth’s community, it’s a signal of real commitment from a major exchange to support the protocol’s growth. And for $PYTH holders, enhanced usage and broader institutional adoption promise stronger utility and relevance.
The marriage of Binance’s infrastructure muscle and Pyth’s data prowess could very well accelerate the shift toward truly global, real-time finance on-chain — and Binance is already in the vanguard of that movement.
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Article 2: How Binance & Pyth Network Can Power the Future of Finance
As blockchain ecosystems mature, the demand for dependable, real-world financial data becomes ever more critical. That’s where Pyth Network (and its native token $PYTH ) steps in — and Binance is stepping up to amplify its impact.
Pyth’s infrastructure & Binance’s role
Pyth aggregates raw price inputs from leading exchanges, trading firms, and financial institutions, then publishes these feeds on-chain across many blockchain networks. Binance already contributes as one of Pyth’s data providers, reinforcing the credibility of the network. Furthermore, Pyth has launched oracles on BNB Chain and Binance Sidechains, enabling any BNB-native app to access 80+ high-fidelity feeds.
Expanding the #PythRoadmap
In its next roadmap phases, Pyth is pushing beyond DeFi into institutional terrains. The launch of Pyth Pro promises subscription access to cross-asset data for traditional firms, with transparent pricing and broad scope (crypto, equities, FX, commodities). Add to that government and agency collaborations — like with the U.S. Department of Commerce — delivering official economic data on-chain, further cementing Pyth’s status as a trusted oracle.
Benefits & implications
For Binance ecosystem: stronger data infrastructure supports derivatives, lending, prediction markets, and more on BNB Chain apps.
For developers & dApps: they can pull precise, low-latency price feeds with confidence, reducing reliance on external or less secure oracles.
For $PYTH holders: increasing real-world usage, staking possibilities, and governance influence may enhance the token’s long-term value.
By weaving Pyth’s oracle capabilities into its fabric, Binance is not just adopting an oracle — it’s building the scaffolding of tomorrow’s finance. With each milestone on the #PythRoadmap, the union of Binance + Pyth edges us closer to a future where on-chain finance mirrors the complexity and depth of traditional systems — but with transparency,
composability, and accessibility baked in.
#pythroadmap $PYTH @Pyth Network
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#pythroadmap @Pyth Network $PYTH Pyth's ultimate vision is to become the core component of Web3 financial infrastructure, similar to Bloomberg terminals (data authority) and SWIFT (global settlement network) in traditional finance. This is achieved through the following ways:
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Data democratization: Allowing global developers to access real-time, reliable financial market data without relying on centralized institutions.
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Standardization and governance: Achieving data source upgrades, fee mechanisms, and other on-chain governance through Pyth DAO, ensuring the network's neutrality and sustainability.
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Value capture: PYTH token holders participate in network governance, while data users pay small fees to maintain ecological operation, forming a positive cycle.
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Data democratization: Allowing global developers to access real-time, reliable financial market data without relying on centralized institutions.
•
Standardization and governance: Achieving data source upgrades, fee mechanisms, and other on-chain governance through Pyth DAO, ensuring the network's neutrality and sustainability.
•
Value capture: PYTH token holders participate in network governance, while data users pay small fees to maintain ecological operation, forming a positive cycle.
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@Pyth Network #pythroadmap $PYTH Pyth's technical vision revolves around high performance, low latency, and decentralization. Key breakthroughs include:
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Push-Pull hybrid data distribution: combining active pushing of critical data with on-demand pulling of high-frequency data to reduce on-chain storage costs and gas fees.
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Entropy V2 performance upgrade: random request processing capability increased by 300%, supporting real-time risk control needs of large-scale DeFi applications (such as derivatives and insurance protocols).
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MEV resistance design: through products like Express Relay, bundling price data with sensitive transactions to reduce miner extractable value (MEV) attacks.
•
Push-Pull hybrid data distribution: combining active pushing of critical data with on-demand pulling of high-frequency data to reduce on-chain storage costs and gas fees.
•
Entropy V2 performance upgrade: random request processing capability increased by 300%, supporting real-time risk control needs of large-scale DeFi applications (such as derivatives and insurance protocols).
•
MEV resistance design: through products like Express Relay, bundling price data with sensitive transactions to reduce miner extractable value (MEV) attacks.
See original
Pyth's brand new roadmap is out, targeting the $50 billion institutional market
1️⃣ Phase One: Laying the foundation — Leading DeFi, creating valuable data sources ✅ (Completed)
2️⃣ Phase Two: Unlocking the $50 billion institutional market 🔥 (In progress)
👉 The biggest highlight is that the revenue model may be directly linked to $PYTH , rumors suggest there may be a buyback logic
3️⃣ Phase Three: Becoming the Price Layer for the global market 🌍 (Next target)
In summary:
In DeFi, Pyth has already proven itself; whether to invest real money into TradFi depends on the wallets of institutions and the value capture mechanism of $PYTH .20
@Pyth Network #pythroadmap $PYTH
1️⃣ Phase One: Laying the foundation — Leading DeFi, creating valuable data sources ✅ (Completed)
2️⃣ Phase Two: Unlocking the $50 billion institutional market 🔥 (In progress)
👉 The biggest highlight is that the revenue model may be directly linked to $PYTH , rumors suggest there may be a buyback logic
3️⃣ Phase Three: Becoming the Price Layer for the global market 🌍 (Next target)
In summary:
In DeFi, Pyth has already proven itself; whether to invest real money into TradFi depends on the wallets of institutions and the value capture mechanism of $PYTH .20
@Pyth Network #pythroadmap $PYTH
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2027 Pyth Network's Institutional-Level Data Subscription Innovation
• Innovation Direction: Launching Phase Two subscription products in 2027, providing customized real-time data feeds without reliance on third-party nodes, unlocking a market potential of $50 billion.
• Data Coverage and Technology: Data publishers expanded from over 120 (such as Binance, Jane Street) to over 200, covering stocks, foreign exchange, and derivatives; enhanced data with confidence intervals provided through Hermes API, supporting RWA tokenization, expected to bridge trillion-dollar traditional assets.
• Token Mechanism: PYTH drives DAO revenue sharing, stakers receive subscription fee rewards, and a deflationary mechanism supports a price peak of $4.52; integrated ZK proofs to prevent data manipulation, multi-chain deployment ensures immutability.
• Applications and Results: Pull-based architecture reduces costs by 90%, empowering on-chain settlements like Revolut; expected to handle transaction volumes exceeding $1 trillion in 2027, transitioning from DeFi tools to global financial infrastructure.
@Pyth Network #pythroadmap $PYTH
• Innovation Direction: Launching Phase Two subscription products in 2027, providing customized real-time data feeds without reliance on third-party nodes, unlocking a market potential of $50 billion.
• Data Coverage and Technology: Data publishers expanded from over 120 (such as Binance, Jane Street) to over 200, covering stocks, foreign exchange, and derivatives; enhanced data with confidence intervals provided through Hermes API, supporting RWA tokenization, expected to bridge trillion-dollar traditional assets.
• Token Mechanism: PYTH drives DAO revenue sharing, stakers receive subscription fee rewards, and a deflationary mechanism supports a price peak of $4.52; integrated ZK proofs to prevent data manipulation, multi-chain deployment ensures immutability.
• Applications and Results: Pull-based architecture reduces costs by 90%, empowering on-chain settlements like Revolut; expected to handle transaction volumes exceeding $1 trillion in 2027, transitioning from DeFi tools to global financial infrastructure.
@Pyth Network #pythroadmap $PYTH
See original
In the traditional world, data is the silent oil, deeply buried and monopolized by giants. In the PYTH network, data is flowing like living water, and the PYTH token is the alchemy that turns stone into gold.
Top exchanges and market makers, as data providers, continuously supply the network with the most original and active price information streams. They are not doing this out of charity, but are driven by sophisticated token economics. Every timely and accurate data push earns PYTH tokens as a reward. This ensures that the data source's "living water" is not only continuous but also of very high quality (in terms of quality and frequency).
Data researcher Anna is looking for the most reliable oracle for her DeFi protocol. She chooses PYTH because she knows that behind every price feed is the endorsement of top global institutions using their reputation and real money, and the driving force behind all this is anchored in the value of the PYTH token.
The fees paid by Anna do not disappear into a company's financial report. They flow into the protocol's treasury, forming the source of value return. Here, data is alchemized into trust, trust is then turned into value, and value ultimately nourishes every builder of the network. $PYTH
@Pyth Network #pythroadmap
Top exchanges and market makers, as data providers, continuously supply the network with the most original and active price information streams. They are not doing this out of charity, but are driven by sophisticated token economics. Every timely and accurate data push earns PYTH tokens as a reward. This ensures that the data source's "living water" is not only continuous but also of very high quality (in terms of quality and frequency).
Data researcher Anna is looking for the most reliable oracle for her DeFi protocol. She chooses PYTH because she knows that behind every price feed is the endorsement of top global institutions using their reputation and real money, and the driving force behind all this is anchored in the value of the PYTH token.
The fees paid by Anna do not disappear into a company's financial report. They flow into the protocol's treasury, forming the source of value return. Here, data is alchemized into trust, trust is then turned into value, and value ultimately nourishes every builder of the network. $PYTH
@Pyth Network #pythroadmap
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