I. Industry Foundation and Development Context: Why Oracles are the "Intelligence Hub" of Blockchain

The essence of blockchain is a decentralized trust machine that ensures the immutability of on-chain data and the autonomy of the system through consensus mechanisms, cryptographic algorithms, and distributed ledger structures. However, due to its closed and self-consistent nature, blockchain cannot actively access off-chain data. From weather forecasts to financial prices, from voting results to off-chain identity verification, on-chain systems cannot "see" or "know" changes in the external world. Therefore, oracles serve as the information bridge between on-chain and off-chain, playing a key role in "perceiving the external world." They are not merely data couriers but the intelligence hub of blockchain—only when the off-chain information provided by oracles is injected into smart contracts can the on-chain financial logic be executed correctly, thus connecting the real world with the decentralized universe.

1.1 Information Islands and the Birth Logic of Oracles

Early Ethereum or Bitcoin networks faced a fundamental problem: on-chain smart contracts are "blind." They can only compute based on data already written to the chain and cannot "actively" obtain any off-chain information. For example: DeFi protocols cannot independently obtain the real-time price of ETH/USD; GameFi games cannot synchronize the scores of real-world events; RWA protocols cannot determine whether real assets (such as real estate or bonds) are liquidated or transferred.

The emergence of oracles is precisely to solve this fatal flaw of information islands. They fetch data from the external world and transmit it to the chain in either centralized or decentralized ways, giving smart contracts "context" and "world state," thus enabling more complex and practical decentralized applications.

1.2 Three Key Evolution Stages: From Centralization to Modularity

The development of oracle technology has gone through three stages, each significantly expanding its role boundaries in the blockchain world:

First Stage: Centralized Oracles: Early oracles mostly adopted a single data source + central node push model, such as early Augur and Provable, but had very low security and censorship resistance, making them easy to tamper with, hijack, or suffer from faults.

Second Stage: Decentralized Data Aggregation (Chainlink Paradigm): The emergence of Chainlink elevated oracles to a new height. It built a decentralized data provisioning network through multiple data providers (Data Feeds) + node networks aggregation + staking and incentive mechanisms. Security and verifiability were greatly enhanced, forming the industry mainstream.

Third Stage: Modular, Verifiable Oracles: With the growth of demand and the emergence of new technologies like AI, modular oracles have become a trend. Projects such as UMA, Pyth, Supra, RedStone, Witnet, Ritual, and Light Protocol have proposed innovative mechanisms including "Crypto-Proofed Data," "ZK-Proofs," "off-chain computation verification," and "custom data layers," evolving oracles towards flexibility, composability, low latency, and auditability.

1.3 Why are Oracles Considered "Intelligence Hubs" Rather than "Peripheral Tools"?

In traditional narratives, oracles are often likened to the "sensory system of blockchain," meaning the eyes, ears, nose, and tongue of blockchain. However, in the current highly complex on-chain ecosystem, this metaphor is no longer sufficient: in DeFi, oracles determine the "benchmark reality" for liquidation, arbitrage, and trade execution; data delays or manipulation can directly trigger systemic risks; in RWA, oracles bear the synchronization function of "off-chain asset digital twins," being the only proof interface for the legitimate existence of real assets on-chain; in the AI + Crypto field, oracles become the "data mouthpiece" for feeding models, determining whether intelligent agents can operate effectively; in cross-chain bridges and re-staking protocols, oracles also shoulder the tasks of "cross-chain state synchronization," "security guidance," and "verifying consensus correctness."

This means that oracles are no longer just "sensors," but the neural hub and intelligence network in the complex on-chain ecosystem. Their role is no longer merely to "perceive," but to establish the infrastructure core for consensus reality, synchronizing the on-chain universe with the off-chain world.

From a national perspective, data is the oil of the 21st century, and oracles are the channel controllers of data flow. Controlling the oracle network means controlling the generation of "reality cognition" on-chain: who defines prices, who masters financial order; who synchronizes truth, who constructs cognitive structures; who monopolizes entry, who defines the standards for "trusted data." Therefore, oracles are becoming the core infrastructure in DePIN, DeAI, and RWA modules.

II. Market Landscape and Project Comparison: The Confrontation between Centralized Legacy and Decentralized Newcomers

Although oracles are regarded as the "intelligence hub" of blockchain, in reality, the controllers of this hub have long been in a sort of "quasi-centralized" monopoly state. Traditional oracle giants represented by Chainlink are both the creators of industry infrastructure and the biggest beneficiaries of order rules. However, with the rise of modular narratives, DePIN paradigms, ZK verification paths, and other emerging trends, the market landscape for oracles is undergoing a significant power reconstruction. The changes in this field are not merely a competition of products but a philosophical confrontation over "who defines on-chain reality."

The significance of Chainlink in the oracle track is akin to the symbolic status of early Ethereum in smart contracts. It was the first to establish a complete network architecture based on the combination of data aggregation, node staking, and economic incentives, becoming an irreplaceable "on-chain benchmark reality provider" after the DeFi summer. Whether it is financial protocols like Aave, Compound, and Synthetix, or Layer 2 networks like Polygon and Arbitrum, a large number of systemic operations heavily rely on Chainlink's data supply. However, this "indispensability" brings two hidden dangers: first, over-reliance leads to single point failure risks for on-chain systems; second, the transparency crisis and data censorship space brought about by implicit centralization. Although Chainlink's node network is nominally decentralized, its actual operation often concentrates on a few validators, such as Deutsche Telekom, Swisscom, Blockdaemon, and other traditional institutional nodes; meanwhile, its Off-Chain Reporting (OCR) mechanism, data source selection, and update frequency decisions are mostly opaque and difficult to govern by the community. It resembles a central publishing system that inputs "trusted version reality" into the blockchain world, rather than a truly decentralized, censorship-resistant data supply market. This has opened up a value breakthrough for later entrants.

The emergence of Pyth Network is a deep counter to the Chainlink model. Pyth does not simply replicate the traditional data aggregation paradigm but directly returns the power of data uploading to the data sources themselves, such as exchanges, market makers, and infrastructure providers. This "first-party data source upload" model significantly reduces the relay layer of data off-chain, improving real-time performance and originality, and transforming oracles from "data aggregation tools" into "raw pricing infrastructure." This is highly attractive for high-frequency, low-latency scenarios such as derivatives trading, perpetual contracts, and on-chain game logic. However, it also raises a deeper issue: many of Pyth's data sources come from crypto exchanges and liquidity providers—these participants are both information providers and market participants. Whether this "being both athlete and referee" structure can truly escape price manipulation and conflicts of interest is an unverified trust gap.

In contrast to Pyth's focus on data sources and update efficiency, RedStone and UMA choose to take a different approach, targeting the structural layer of the oracle "trust path" itself. The operational mechanism of traditional oracles is mostly based on "price feeding" and "confirmation," meaning that nodes upload data and broadcast it to smart contracts, which directly use this data as a basis for state. The biggest problem with this mechanism is that there is no real "data verifiable path" on-chain. In other words, contracts cannot determine whether the uploaded data truly originates from the specified off-chain information source, nor can they audit whether its path is complete and neutral. The "verifiable data packet" mechanism proposed by RedStone addresses this issue: by encrypting off-chain data into a data body with a signature verification structure, which is then unpacked and verified by executing contracts in real-time, thus greatly enhancing the certainty, security, and flexibility of on-chain data calls.

Similarly, the "Optimistic Oracle" paradigm advocated by UMA is even more radical. It assumes that oracles do not need to provide absolutely correct data every time but introduce economic games to resolve disputes when they arise. This optimistic mechanism delegates most data processing logic to off-chain, only returning to on-chain governance through a dispute arbitration module when disagreements occur. The advantage of this mechanism lies in its high cost efficiency and system scalability, making it suitable for complex financial contracts, insurance protocols, and long-tail information scenarios, but its drawbacks are also very apparent: if the incentive mechanism design within the system is inadequate, it is easy for attackers to repeatedly challenge and manipulate the oracle through game manipulation.

Emerging projects like Supra, Witnet, and Ritual are innovating on finer dimensions: some are building bridges between "off-chain computation" and "cryptographic verification paths," some are attempting to modularize oracle services so they can be freely nested into different blockchain operating environments, and others are rewriting the incentive structure between nodes and data sources to form a "custom supply chain" for on-chain trusted data. These projects have not yet formed mainstream network effects, but they reflect a clear signal: the oracle track has shifted from a "battle for consensus" to a "battle for trust paths," from "single price provision" to a comprehensive game of "trusted reality generation mechanisms."

We can see that the oracle market is undergoing a transformation from "infrastructure monopoly" to "trust diversity." Established projects have strong ecological binding and user path dependence, while emerging projects leverage verifiability, low latency, and customization to attempt to exploit the gaps left by centralized oracles. However, regardless of which side one stands on, we must acknowledge a reality: whoever can define "truth" on-chain holds the benchmark control of the entire crypto world. This is not a technical war but a "battle for definition rights." The future of oracles is destined to be more than just "moving data onto the chain."

III. Potential Space and Boundary Expansion: From Financial Information Flow to On-Chain RWA Infrastructure

The essence of oracles is to provide "verifiable reality inputs" for on-chain systems, which gives them a core role in the crypto world that goes far beyond data transmission. Looking back over the past decade, oracles have evolved from initially serving the "price feeding" function in decentralized finance (DeFi) to expanding into broader boundaries: from being the basic data providers for on-chain financial transactions to becoming the central systems for mapping real-world assets (RWA), cross-chain interoperability bridge nodes, and even supporting complex structures such as on-chain law, identity, governance, and AI-generated data.

The Infrastructure of Financial Information Flow: During the golden period of DeFi's rise (2020-2022), the primary role of oracles focused on "price feeding"—providing real-time prices of external market assets for on-chain contracts. This demand drove the rapid development of projects like Chainlink, Band Protocol, and DIA, also giving birth to the first generation of oracle standards. However, in actual operation, the complexity of DeFi contracts continued to escalate, forcing oracles to "go beyond prices": insurance protocols require climate data, CDP models need economic indicators, perpetual contracts need volatility and transaction volume distributions, and structured products require complex multi-factor data. This marks the evolution of oracles from price tools to access layers for diverse data sources, and their role is gradually becoming "systematized."

Furthermore, with projects like MakerDAO, Centrifuge, Maple, and Ondo massively introducing off-chain debts, government bonds, and fund shares as real assets, the role of oracles is beginning to evolve into trusted registrars for on-chain RWA. In this process, oracles are no longer merely "pipes for inputting data," but become the certifiers, state updaters, and yield distributors of RWA on-chain—a neutral system with "fact-driven capabilities."

The Trustworthiness of On-Chain RWA: The biggest issue with RWA has never been "technical difficulty," but rather "how to align on-chain representations with off-chain legal and asset states." In traditional systems, this consistency relies on lawyers, audits, regulations, and paper processes for assurance, while on-chain, oracles become the key to reconstructing this mechanism. For example, if an on-chain bond is secured by a set of off-chain real estate, how does the smart contract know whether that property has been seized, appraised, rented, sold, or mortgaged to others? All this information exists off-chain and cannot be natively put on-chain. At this point, the task of oracles is no longer simply to "synchronize data," but to build an "on-chain trust snapshot" by connecting government registration systems, IoT devices, audit processes, and reputation mechanisms. They must continuously refresh this snapshot to ensure the consistency between contract states and real-world states. This capability pushes oracles toward more complex application boundaries, even requiring the integration of legal, physical, and political trust systems.

At the same time, we also see collaborations like RedStone and Centrifuge, which upload cash flows, maturity statuses, and default information of RWA assets in a modular data format to the chain, providing atomic-level inputs for transactions, risk control, and settlement in liquidity markets. This standardization of data and trusted updating mechanisms is almost equivalent to building "audit chips" for the on-chain financial system, serving as the foundation for the entire on-chain financial ecosystem to map to reality.

The Evolution of Oracles Across Asset Layers: Another noteworthy trend is that oracles are gradually evolving from "data provision layers" for assets to "cross-asset coordination layers." Against the backdrop of the rapid rise of cross-chain protocols like LayerZero and Wormhole, single-chain data barriers have begun to be broken, but there still exists a serious gap in the synchrony of asset states. For example, a stablecoin on Ethereum may rely on a liquidation price on Arbitrum, while a structured product on Solana may involve the yield of RWA debts on Polygon. This multi-chain interactive financial structure requires a "logical hub" to coordinate data acquisition, updates, verification, and broadcasting. Future oracles, especially those supporting cross-chain deployment, off-chain collaboration, and composable contract structures, will resemble an "on-chain API platform"—not just providing data but possessing the capabilities to call, verify, transform, integrate, and distribute, thus becoming the data intelligence layer of the entire Web3 application layer.

Once oracles achieve stability on RWA, the next boundary will be the data mapping of "people" and "behavior." In other words, they will not only record "the state of things" but also capture "human behavior"—on-chain credit systems, DID (decentralized identity), on-chain litigation arbitration, and even the authenticity verification of AI-generated content will all require "auditable on-chain input ports." This direction has already begun to show signs in projects like EigenLayer, Ritual, and HyperOracle: they either allow oracles to verify off-chain model outcomes, or connect AI model outputs to on-chain element processes, or enable auditors to assume factual responsibility through staking.

This trend indicates that the boundaries of oracles have expanded from "financial information flow" to the entire data map of "on-chain order generation," becoming the infrastructure for the real world to transition to on-chain civilization. They are no longer just a megaphone for transmitting prices but a digital bridge linking information, value, and trust.

IV. Trend Outlook and Investment Recommendations: Structural Opportunities Have Arrived, Focus on Three Key Directions

The technological maturity and industry attention of oracles often exhibit characteristics of "non-linear traversal cycles"—after public chain infrastructure enters a phase of stock competition, oracles, as the core "data base" linking the real world on-chain, have instead gained a stronger strategic position. Whether it is the rise of Layer 2, the landing of RWA, or the combination of AI and on-chain computation, oracles have become unavoidable "trust anchors." Therefore, looking ahead to the next three years, the investment logic in the oracle track will shift from "market cap imagination during the hype phase" to "cash flow value reassessment brought by structural growth."

4.1 Structural Trends Are Clear, Supply and Demand Curves Re-Matched

As traditional financial institutions and on-chain protocols accelerate their integration, the asset states, legal statuses, and behavioral states of the real world off-chain must enter on-chain systems in a structured, standardized, and verifiable manner. This trend has brought about two fundamental changes:

1. The demand for high-frequency, customized data streams has surged; oracles are no longer simple price relay systems but computing nodes that support a series of complex logics (such as automatic liquidation, yield mapping, state changes);
2. The "economic attributes" of data have become more prominent, with pricing models gradually transitioning from "Gas costs + node incentives" to "B2B enterprise-level subscriptions + SLA data agreements + commercial contract responsibilities," forming stable cash flows.

The leap in supply-demand relationships directly drives project valuation models from "narrative-driven" to "revenue-driven," also providing new investment anchors for long-term holders and strategic funds. Especially for leading RWA projects, AI computing chains, and DID architectures, choosing reliable, stable, and high-throughput oracle service providers becomes an irreplaceable dependency at the contract level.

4.2 Three Key Directions Have Long-Term Alpha Potential

In this new development paradigm, we recommend focusing on three types of oracle development paths, each representing the extension capabilities of oracles as the on-chain "intelligence hub" in different dimensions:

1. Modular, Application-Side Native Oracles: Close to business means close to value: compared to traditional "general-purpose" oracle models, new-generation projects like RedStone, Pyth, and Witnet emphasize "on-demand services" and "on-site deployment," embedding oracle logic into application contracts or VM layers. This model better matches the needs of high-frequency trading and structured asset protocols, making data transmission faster, responses more accurate, and costs lower. The advantage of these projects lies in their natural "product-protocol" stickiness; once a DeFi or RWA project selects a certain type of oracle, the migration cost is extremely high, meaning long-term binding returns and defensive moats.

2. AI and Oracle Integration Narrative: The interface layer for verification, filtering, and fact generation: as AI models widely intervene in the crypto ecosystem, how to verify the authenticity of generated content, behavioral predictions, and external calls becomes an unavoidable foundational issue. Oracles are the "logical anchor" for this problem: they not only provide data but can also verify whether the data comes from a trusted computing process and whether it meets multi-party consensus mechanisms. Projects like HyperOracle, Ritual, and Aethos have begun to explore ways to provide "provable AI call results" for on-chain contracts through zkML, trusted hardware, and cryptographic reasoning, integrating as oracles on-chain. This direction has high technical barriers and high capital attention, making it a potential ignition point for the next round of high Beta.

3. RWA and Identity-Bound Oracles: Off-chain legal status mappers: from the asset universal message standard established by Chainlink and Swift, to the multi-asset yield status synchronization on Centrifuge, to Goldfinch introducing third-party assessment models, RWA is rapidly constructing a trusted mechanism relying on a "neutral information layer." The core of this mechanism relies on oracle systems that can credibly put off-chain legal, asset registration, and behavioral credit content on-chain. These projects lean more towards "infrastructure" logic, and their development paths are highly related to regulatory policies. However, once an industry standard is formed (like Chainlink's CCIP), they will possess exponential network effects, making them suitable for long-term layout as "gray consensus assets."

4.3 Investment Logic Reconstruction: From "Price Feeding Narrative" to "On-Chain Order" Pricing

In the past, the market often regarded oracles as "ancillary tools in the DeFi hotspot track," with market cap assessments and investment behaviors mostly fluctuating with the overall market. However, in the future, oracles themselves will gradually gain independent value assessment mechanisms, due to their role as irreplaceable fact injectors in on-chain protocols; they possess stable, quantifiable sources of protocol income (such as Chainlink's data pricing model has formed a B2B commercial subscription logic); and they undertake the underlying information coordination tasks in multiple structural growth tracks like RWA, AI, and governance, exhibiting multiplier effects.

Therefore, we recommend that investors should not only evaluate projects based on "market cap size" and "trading heat," but should filter oracle assets with long-term value potential based on the following three main lines: whether they have a native deep binding with protocols, chains, and financial institutions; whether they have established a commercial closed loop of "data-facts-consensus"; and whether they possess scalability advantages in next-generation scenarios (RWA, AI, cross-chain).

In summary, oracles are no longer the supporting roles on the margins of crypto narratives but are gradually moving towards becoming the "fact benchmark system" and "order generation engine" of the on-chain world. Structural opportunities have already formed, and investment logic urgently needs to be reconstructed.

V. Conclusion: The Era of Structural Dividends in the Oracle Track Has Arrived

The oracle track is standing at the forefront of the evolution of the blockchain ecosystem, bearing the core role of bridging information between the on-chain world and the real world. As the complexity of on-chain applications and the demand for real asset on-chain increases, oracles are no longer just price data providers but have become the "intelligence hub" and "order generation engine" for the trusted execution of smart contracts. The multidimensional enhancement of technology and the deep expansion of application scenarios have brought unprecedented development space and value reassessment opportunities for oracles.

In the future, oracle projects will develop towards more decentralized, modular, and scenario-based directions. The integration of AI and on-chain data, as well as the on-chaining process of RWA, will inject continuous growth momentum into them. Investors should examine the value of oracle projects from the three dimensions of on-chain protocol binding, business model closed loops, and scalability, focusing on innovative forces with long-term moats and structural growth potential. Overall, the oracle track has gradually shifted from a supporting role to the "intelligence hub" of the blockchain world, and its ecological value and investment opportunities should not be overlooked; the era of structural dividends has already arrived.