I. Industry Basics 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 inherently 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 critical bridge of information between on-chain and off-chain, playing a key role in "perceiving the external world." They are not merely data transporters but the intelligence hub of blockchain—only when off-chain information provided by oracles is injected into smart contracts can 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 perform calculations based on data already written to the chain and cannot "actively" obtain any off-chain information. For example: DeFi protocols cannot independently obtain real-time ETH/USD prices; GameFi games cannot synchronize scores from real-world events; RWA protocols cannot determine whether real assets (such as real estate or bonds) are liquidated or transferred.
The emergence of oracles was precisely to solve this fateful flaw of information islands. They fetch data from the external world and transmit it to the chain in either a centralized or decentralized manner, giving smart contracts "context" and "world state," thus enabling more complex and practical decentralized applications.
1.2 Three Key Evolutionary 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 new heights. It built a decentralized data provision network through multiple data providers (Data Feeds) + node network 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 "digital twins of off-chain assets," serving as the only proof interface for the legitimate existence of real assets on-chain; in the AI+Crypto field, oracles become the "data mouth" 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 within 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 network of oracles means controlling the generation of "realistic cognition" on-chain: who defines prices, who masters financial order; who synchronizes truth, who constructs cognitive structures; who monopolizes entry, who defines the standards of "trusted data." Therefore, oracles are becoming the core infrastructure in DePIN, DeAI, and RWA modules.
II. Market Landscape and Project Comparison: The Direct Confrontation of Centralized Legacies 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 state of quasi-centralized monopoly. Traditional oracle giants represented by Chainlink are both the creators of industry infrastructure and the biggest beneficiaries of the 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 about product competition but a philosophical confrontation over "who defines on-chain reality."
The significance of Chainlink in the oracle space 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" also brings two hidden risks: first, over-reliance leads to single point failure risks in 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, and Blockdaemon; and 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 a value breakthrough for later entrants.
The emergence of Pyth Network is a deep counter to the Chainlink model. Pyth does not 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 layers of data off-chain, improving real-time performance and originality, and transforming oracles from "data aggregation tools" to "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: Pyth's data sources mostly 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 remains 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, delving into the structural layer of the oracle "trust path" itself. The operational mechanism of traditional oracles is often 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 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 instead introduces economic games to resolve disputes when they arise. This optimistic mechanism delegates most data processing logic 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 to encounter issues of attackers repeatedly challenging and manipulating the oracle.
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 service modules so they can be freely nested into different blockchain operating environments, and some are even rewriting the incentive structure between nodes and data sources to form a "custom supply chain" of trusted on-chain data. These projects have not yet formed mainstream network effects, but they reflect a clear signal: the oracle space has shifted from a "battle of consensus" to a "battle of 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 use verifiability, low latency, and customization as weapons to attempt to cut through the cracks left by centralized oracles. But 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 technological war but a battle for "definitional power." 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 real-world inputs" for on-chain systems, which allows them to take on 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 foundational 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.
Infrastructure for 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, giving rise to the first generation of oracle standards. However, in practice, 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, with their role gradually becoming "systematized."
Furthermore, with projects like MakerDAO, Centrifuge, Maple, and Ondo massively introducing off-chain debts, government bonds, fund shares, and other real-world assets, the role of oracles began to evolve into trusted registrars for on-chain RWA. In this process, oracles are no longer just "pipes for inputting data," but rather the certifiers, state updaters, and yield distributors for RWAs on-chain—a neutral system with "fact-driven capabilities."
The Credibility 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, 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 brought 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 of contract states with 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 that of RedStone and Centrifuge, which upload cash flows, maturity statuses, default information, and other RWA asset data in a modular format to the chain, providing atomic-level inputs for trading, risk control, and settlement in liquidity markets. This standardization of data and credible updating mechanisms is almost equivalent to building "audit chips" for the on-chain financial system, forming 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 the "data provision layer" for assets to the "cross-asset coordination layer." Against the backdrop of the rapid rise of cross-chain protocols like LayerZero and Wormhole, single-chain data barriers have begun to break down, but there remains a significant gap in the synchronization 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 the acquisition, updating, verification, and broadcasting of data. Future oracles, especially those supporting cross-chain deployment, off-chain collaboration, and composable structured oracle systems, will resemble an "on-chain API platform"—not just providing data but possessing the capabilities to call, verify, transform, integrate, and distribute data, thus becoming the data intelligence layer of the entire Web3 application layer.
Once oracles achieve stability in 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, decentralized identities (DID), 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 take shape in projects like EigenLayer, Ritual, and HyperOracle: they either enable oracles to verify off-chain model results, integrate AI model outputs into on-chain element processes, or allow auditors to assume factual responsibility in a staking model.
This trend indicates that the boundaries of oracles have expanded from "financial information flow" to encompass the entire data spectrum of "on-chain order generation," becoming the infrastructure for the real world to transition to on-chain civilization. They are no longer merely a conduit 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 on oracles often exhibit characteristics of "non-linear cycles"—after public chain infrastructure enters a phase of stock competition, oracles, as the core "data foundation" linking the on-chain world to the real world, have instead gained a stronger strategic position. Whether it is the rise of Layer 2, the implementation of RWA, or the combination of AI and on-chain computing, oracles have become unavoidable "trust anchors." Therefore, looking ahead to the next three years, the investment logic in the oracle space will shift from "market cap imagination during the hype phase" to "cash flow value reassessment driven by structural growth."
4.1 Clear Structural Trends, Supply and Demand Curves Realigned
As traditional financial institutions and on-chain protocols accelerate their integration, the asset states, legal statuses, and behavioral states of the real world must enter on-chain systems in a structured, standardized, and verifiable manner. This trend brings about two fundamental changes:
The demand for high-frequency, customized data streams has surged, making oracles no longer a simple price relay system but rather computational nodes supporting a range of complex logics (such as automatic liquidation, yield mapping, and state changes).
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 liabilities," forming stable cash flows.
The leap in supply and demand relationships directly drives project valuation models from "narrative-driven" to "revenue-driven," 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 is an irreplaceable dependency at the contract level.
4.2 Three Key Directions with Long-Term Alpha Potential
In this new development paradigm, we recommend focusing on three types of oracle development paths, each representing the extended capabilities of oracles as the "intelligence hub" on-chain across different dimensions:
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 inherent "product-protocol" stickiness; once a DeFi or RWA project selects a certain type of oracle, the migration costs are extremely high, indicating long-term binding returns and defensive moats.
Narrative of AI and Oracle Integration: The interface layer for verification, filtering, and fact generation: As AI models widely intervene in the crypto ecosystem, how to verify the authenticity of their generated content, behavioral predictions, and external calls has become 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 providing "provable AI call results" for on-chain contracts through zkML, trusted hardware, and cryptographic inference, integrating them into the chain in the form of oracles. This direction has high technical barriers and high capital attention, making it a potential ignition point for the next round of high beta.
RWA and Identity-Bound Oracles: Off-chain legal status mappers: From the asset universal messaging standard developed in collaboration between Chainlink and Swift to the multi-asset yield state synchronization on Centrifuge, and the introduction of third-party evaluation models by Goldfinch, RWA is rapidly constructing a trusted mechanism reliant on a "neutral information layer." The core of this mechanism depends on oracle systems that can credibly bring off-chain legal, asset registration, and behavioral credit information on-chain. These projects lean more towards "infrastructure" logic, with development paths highly correlated to regulatory policies, but once industry standards are formed (like Chainlink's CCIP), they will possess exponential network effects, making them suitable for long-term positioning as "gray consensus assets."
4.3 Investment Logic Reconstruction: From "Price Feeding Narrative" to "On-Chain Order" Pricing
In the past, the market often viewed oracles as "ancillary tools in the DeFi hotspot track," with market cap assessments and investment behaviors largely fluctuating with the overall market. However, in the future, oracles themselves will gradually gain independent value assessment mechanisms, due to their irreplaceable role as fact injectors in on-chain protocols; they possess stable, quantifiable sources of protocol revenue (such as Chainlink's data pricing model has formed a B2B commercial subscription logic); and they undertake foundational information coordination tasks in multiple structural growth tracks like RWA, AI, and governance, exhibiting multiplier effects.
Therefore, we recommend that investors should not only assess 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 "data-fact-consensus" commercial closed loop; and whether they possess scalability advantages in next-generation scenarios (RWA, AI, cross-chain).
In summary, oracles are no longer the supporting characters 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 Space Has Arrived
The oracle space stands at the forefront of the evolution of the blockchain ecosystem, playing a core role in 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 deepening 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, with the integration of AI and on-chain data, and the on-chaining process of RWA will inject continuous growth momentum. 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 space 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.
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