Part 1 – Introducing the Problem

The Invisible Impact of Decentralized Oracles: How They Are Reshaping Data Access and Reliability in Blockchain Ecosystems

Part 1 – Introducing the Problem

If blockchains are immutable ledgers, oracles are their most dangerous dependency. Despite what trustless systems promise, the majority still rely on off-chain data feeds—their weakest link—gated by opaque infrastructure and unverifiable logic. Decentralized oracles were proposed to fix this, but in practice, their role has quietly become one of the most under-scrutinized yet foundational elements in Web3 data integrity, financial security, and interchain communication.

The core issue? Blockchains are deterministic. They cannot natively access external data such as asset prices, weather events, or game states. The workaround—using oracles—introduces an attack surface where incorrect information can trigger billions in unintended consequences. We’ve seen this unfold in flash loan exploits, manipulated price feeds, and consensus failures. What’s unsettling is how casually these vulnerabilities are passed off as edge cases, when in fact they are central flaws.

In the early days of smart contracts, centralized oracles sufficed for experimentation. But as capital, users, and system criticality increased, the limitations became structural. The reliance on trusted third parties directly contradicts decentralization’s ethos and exposes DeFi to manipulation akin to TradFi’s darkest days—only on-chain and irreversible.

While protocols like Tellor and Chainlink pioneered decentralized oracle networks, many operate with assumptions of honesty from node participants, without solving the data provenance issue. In most models, participants vote or stake on data, but objective truth becomes subjective consensus—a dangerous abstraction when pegging collateral or automating derivatives.

Even in diagram-heavy whitepapers, oracle networks often gloss over the real question: how is external data verified before it shapes on-chain logic? Without machine-verifiable provenance—a way to trace and authenticate data from origin to consumption—we’re back to Web2 with extra steps. The blockchain becomes a decentralized execution layer with a centralized input layer.

Projects like the XYO Network show a different approach, anchoring data with spatial and temporal proofs. But even these systems struggle with ensuring auditability at scale, especially when multi-chain deployment complicates integrity guarantees. Worse, multi-step cross-chain oracles entrench complexity, increasing fragility instead of distributing trust.

As more Web3 applications outsource crucial logic to oracles, the industry’s blind spot becomes a systemic risk. This isn’t just about price feeds anymore—it’s about the very notion of what data is considered “truth” on-chain.

Decentralized oracle design hasn’t matured to the level of its financial or consensus counterparts. And until it does, data reliability remains the weakest pillar in blockchain infrastructure architecture.

Part 2 – Exploring Potential Solutions

Zero-Knowledge Proofs, Threshold Cryptography, and the Race to Reliable Oracle Design

As decentralized oracles continue grappling with the fundamental trilemma of data availability, accuracy, and trust minimization, several architectures are emerging to challenge the single-point-failure paradigm. Layered cryptographic proofs and game-theoretic incentives are at the core of these developments.

1. Zero-Knowledge Middleware Architectures

Zero-knowledge rollups like zkOracles attempt to verify oracle behavior without disclosing the underlying data sources. By leveraging SNARKs or STARKs, nodes can prove that they followed protocol rules (e.g., consensus on data feeds) without exposing the raw data, offering minimized trust assumptions.

The strength of this setup lies in verifiability. Consumers of on-chain data don’t have to trust a node; they only need to verify the proof. However, the limitation is computational friction. Generating and verifying these proofs remains resource-intensive—making them prohibitive for high-frequency, low-latency data like price feeds or geospatial data.

Projects like Tellor and Chainlink remain encumbered by the need for off-chain trust assumptions here, showing that zk-based approaches are promising but not yet ready at scale. This opens the field for more adaptive cryptographic composites that balance speed and truthfulness.

2. Threshold Cryptography for Multi-Signature Aggregation

Rather than relying on a single oracle provider, multiple oracle nodes sign digital attestations, requiring a predefined quorum to aggregate before relaying to a smart contract. Threshold signatures via BLS or EDDSA aggregates prevent single-node manipulation and are effective against collusion—if the validator set is sufficiently decentralized.

This method is performant, resistant to Sybil attacks, and audit-proof. But key management is fragile. If one threshold private key leaks or becomes entrapped due to slashing misconfigurations, the entire system can be compromised. Moreover, validator collusion remains non-trivial to detect, especially if incentives align or governance is centralized.

3. Data Provenance via On-Chain Anchoring

Some networks explore anchoring raw data provenance using mirrored commitments or hash-based attestations. This model doesn’t solve oracle reliability directly but offers a trail for tamper-evident validations. In layered oracle-vector stacks like in the XYO Network, anchoring location-based proofs on-chain acts as a transparency ledger—auditable but not inherently truthful.

This approach scales well for data-heavy use cases but lacks the enforcement mechanism needed to validate the quality or intent of off-chain data sources.

These theoretical models are converging toward hybrid infrastructures that blend zero-knowledge proofs, threshold cryptography, and economic disincentives. Cross-chain oracle interoperability further complicates these mechanisms, expanding the failure surface but enabling broader composability. While elegant on paper, operationalizing them requires tackling latency, game-theoretic stability, and governance design—topics that will surface in Part 3 as we dissect real-world deployments.

Part 3 – Real-World Implementations

Real-World Implementations of Decentralized Oracles: Case Studies, Constraints, and Architectures

One of the earliest attempts to circumvent centralized oracle risk came from Tellor, a permissionless oracle protocol designed to bridge high-value data onto Ethereum using miner-like reporting incentives. The protocol faced structural latency issues: data reporters had to stake TRB tokens and wait through a dispute window before finalization. This security model emphasized honesty through financial risk, but real-time use cases like on-chain perps and stablecoin pegs found it unusable. Ironically, low-frequency applications—precisely the ones with lower exploit incentive—were its primary adopters. Despite its cryptoeconomic elegance, Tellor struggled with adoption outside its niche. A full technical breakdown can be found in https://bestdapps.com/blogs/news/unlocking-tellor-the-future-of-decentralized-oracles.

Another real-world deployment comes from the XYO Network, which took a geospatial approach. By introducing IoT devices as data attestators, XYO aimed for decentralized, physical-world oracles. In practice, reliable device onboarding and data provenance verification were core obstacles, often compounded by skewed economic incentives and unclear validator accountability. While theoretically robust in edge networks and logistics, XYO’s framework sees limited usage in DeFi protocols today. A full critique and analysis of its assumptions is available in https://bestdapps.com/blogs/news/unpacking-the-critiques-of-xyo-network.

Projects like API3 took a middleware-first strategy, building "first-party" oracles by onboarding traditional data providers directly onto the blockchain. This reduced trust assumptions in third-party aggregators but encountered implementation friction. Many legacy data firms lacked the technical capacity or incentive to deploy and maintain beacon nodes. Moreover, API3’s governance DAO occasionally introduced latency in making urgent system upgrades due to proposal bottlenecks.

Cross-chain oracles have fared no better. Band Protocol, marketed as a high-throughput, Cosmos-SDK-powered alternative to Chainlink, met its architecture’s limits during cascading congestion events on the underlying chain. Delayed data finality rendered Band suboptimal for undercollateralized DeFi loans, where price precision across L1s and L2s is non-negotiable.

Even with technically approved models, adoption remains fragmented. Smart contracts dependent on oracle feeds often require manual integration, and each protocol implements disputes and fallbacks differently. No uniform standard for verification has emerged, making each deployment idiosyncratic and increasing attack surface.

Meanwhile, developers often default to centralized APIs to avoid sluggish oracle setups altogether, especially in the early MVP stage—a centralization compromise most refuse to admit publicly.

Part 4 will delve deeper into whether decentralized oracle systems can evolve past these fragmented and friction-heavy implementations—towards a unified data layer essential for trust-minimized computation at scale.

Part 4 – Future Evolution & Long-Term Implications

The Evolution of Decentralized Oracles: Emerging Pathways in a Fragmented Blockchain Ecosystem

Decentralized oracle networks (DONs) are on the brink of transformative change, driven by efforts to tackle scalability bottlenecks, cross-chain data fragmentation, and the need for robust privacy-preserving mechanisms. While early oracle architectures operated with monolithic assumptions—single-layer consensus and source aggregation—the new wave is pushing toward modular, composable, and use-specific frameworks.

A potent evolution path lies in the integration of Layer-2 and Layer-3 scaling solutions to offload verification costs from L1 chains. Protocol-specific implementations like rollup-friendly oracles are already being explored, using zk-proofs or optimistic validation to batch data feeds with lower trust assumptions. This could significantly reduce gas costs while maintaining economic guarantees—a necessary shift as oracles increasingly serve high-frequency DeFi and gaming environments.

Interoperability remains a glaring issue. Cross-chain communication has historically been weakened by data siloes and lack of unified messaging standards. Solutions are gravitating toward universal data layers, structured around cross-chain message protocols like IBC and wormhole-like bridges. The long-term implication is the birth of meta-oracles—layer-agnostic data validators capable of servicing multiple chains simultaneously. Projects like NODL and Tellor are already rethinking architecture in this direction. Readers seeking a broader context on interoperability may benefit from The Overlooked Importance of Interoperability in Blockchain.

Another focal point is cryptographic confidentiality. Current oracles are mostly transparent, exposing sensitive data to potential MEV or front-running. Confidential computing—through TEEs or zero-knowledge proofs—offers a path forward, albeit with risk tradeoffs. TEEs still rely on trusted hardware, while ZK approaches face size and latency constraints. A promising middle ground being explored is hybrid schemes: ZK verification of TEE-generated attestations.

Economically, there is also the looming question of incentivization. As on-chain demand for external data rises, the token-based security model may buckle under pressure. Protocols are experimenting with dual-token models, sustainable fee markets, and slashing-enabled staking to reinforce reliability. Yet, this adds regulatory and governance complexity—especially in markets where data provision itself may eventually be considered an attested service.

Integration into decentralized identity systems and AI-driven verification layers is also on the horizon. Use cases like geospatial identity and IoT event authentication, outlined in Unlocking Data Integrity in the XYO Network, hint at broader integrations that stretch the role of oracles beyond financial feeds into the trust infrastructure layer of Web3.

This technical evolution will reshape how DONs are governed and contested—issues that will become essential when considering who gets to validate truth in decentralized ecosystems. Governance models, slashing conditions, and collusion mitigation mechanisms will be explored deeper in the following section on decentralization and decision-making.

Part 5 – Governance & Decentralization Challenges

Decentralized Oracle Governance: The Uncomfortable Tradeoffs Behind “Trustless” Data

Decentralized oracles promise cryptographic guarantees for external data feeds—but their governance structures often undermine the very decentralization they claim to protect. As oracle networks scale, the boundary between distributed infrastructure and centralized control becomes porous, exposing the ecosystem to systemic manipulation, opaque decision-making, and even state-level censorship.

On one end of the spectrum lie fully decentralized oracle networks governed via token-based DAOs. In theory, every stakeholder has a proportional say in network upgrades, pricing mechanisms, and data inclusion policies. In practice, these systems commonly prioritize token-weighted voting, opening the doors to plutocratic dominance. Whales and VC-aligned interests can consolidate voting power to steer protocol direction, approve malicious upgrades, or suppress dissenting oracle reporters. Protocols like Tellor and Chainlink have faced scrutiny for such concentrated voting dynamics. In the case of Tellor, some critics have pointed to the risk in TRB’s token-weight model potentially becoming a vector for governance capture, as explored in Tellor TRB Navigating the Future of Blockchain Oracles.

Moving toward a more hybrid model, some networks utilize multisig governance or trusted committees to fast-track decision-making. These keep networks agile but reintroduce central points of failure. Any multisig configuration, no matter how “distributed,” is fundamentally off-chain and opaque—meaning that governance-critical decisions (like slashing oracle nodes or adjusting collateral requirements) can happen without community oversight. Worse still, these structures are especially vulnerable to bribery attacks, legal pressure, and internal collusion.

This is compounded by inconsistencies in how oracle projects define their own governance boundaries. For example, should reporters have veto rights over the data they submit? Can voting participants be anonymous if Sybil resistance mechanisms are weak? Without clear frameworks—many of which are absent in earlier iterative networks that evolved without governance in mind—these questions become flashpoints for community fragmentation or operational breakdowns.

Ultimately, the decentralization of governance is inseparable from the oracle’s security model. If decision-making power is too heavily concentrated or poorly defined, the integrity of the data itself collapses. Purely decentralized systems offer resilience but slow coordination, while centralized committees simplify UX and updates but drift dangerously close to regulatory scrutiny.

These structural challenges mirror issues confronted in other Web3 governance models. For an insightful parallel, see Navigating Governance in the XYO Network, where procedural ambiguity and power asymmetries threaten long-term system sustainability.

As we confront these complexities, the next section will explore the underlying technical scaling barriers and engineering design trade-offs that must be addressed before decentralized oracles can reach mass-market utility.

Part 6 – Scalability & Engineering Trade-Offs

Scalability Bottlenecks and Engineering Trade-Offs in Decentralized Oracles

As decentralized oracles expand their role in blockchain ecosystems, their integration introduces non-trivial scalability challenges. Unlike on-chain logic, which benefits from deterministic consensus, oracles operate in off-chain environments and require trustless data bridging—a process both compute-heavy and latency-sensitive. The resulting architecture must reconcile decentralization, data throughput, and network integrity in real-time—not an easy feat on base-layer blockchains strained by throughput ceilings.

One fundamental engineering trade-off lies in choosing between push-based and pull-based oracle models. Push-based designs (as seen in high-frequency data feeds) can flood a network with updates, burdening gas-constrained environments like Ethereum L1. Pull-based models alleviate congestion but introduce latency, which may be unacceptable for use cases like derivatives or liquidation triggers in DeFi platforms.

Consensus mechanism selection intensifies this tension. PoS chains (e.g., Solana, Avalanche) deliver impressive throughput for oracle networks but at the cost of validator centralization—exposing oracle feeds to coordinated data manipulation. In contrast, PoW networks such as Bitcoin are extremely secure and decentralized but provide inadequate transaction speed for dynamic feeds, rendering real-time oracles nearly unusable without costly off-chain workarounds.

Additionally, Layer 2 optimism does not absolve oracles from throughput concerns. In rollup environments, data availability becomes the bottleneck. Even if the oracle protocol offloads computation, the necessity to anchor proofs or dispute responses on L1 congests capacity at scale. Oracle projects that support fraud-proof or zero-knowledge oracle verification mechanisms increase demand for complex cryptographic operations—amplifying node requirements and narrowing the pool of participants, thereby compromising decentralization.

Horizontal scaling, such as sharded oracles or subnet-based deployments, may relieve some load but fragments consensus guarantees. Cross-shard coordination reintroduces latency and failure vectors, effectively decoupling time-sensitivity from oracle completeness. This design wrangle is evident in ecosystem-specific oracles like the ones used in the XYO Network. For an inspection into how geo-spatial constraints complicate oracle decentralization, read Unpacking the Critiques of XYO Network.

Resource-intensive staking also imposes a ceiling on scalability. High collateral requirements limit participation, especially when paired with slashing mechanisms, which may deter smaller data providers—a critical group for decentralization. Capital efficiency suffers unless balanced with dynamic reward mechanisms, such as those found on platforms offering staking-based referral programs like Binance.

Scalability will remain a choke point until oracle networks engineer a more balanced triad between decentralization, security, and latency guarantees. The next section will examine how these architectural decisions intersect with regulatory landscapes, particularly focusing on compliance and jurisdictional risk.

Part 7 – Regulatory & Compliance Risks

Smart Contracts Under Scrutiny: Regulatory and Compliance Risks in Decentralized Oracle Adoption

Despite the technological sophistication behind decentralized oracles, the legal framework surrounding their deployment is anything but mature. These systems, which mediate between off-chain data and on-chain execution, inherently blur lines between data publishers, protocol operators, and smart contract enforcers. As jurisdictional oversight increases, the lack of clear accountability nodes in decentralized oracle networks may expose developers and node operators to unexpected litigation or compliance burdens.

A critical vulnerability surfaces around jurisdictional overlap. Oracles that fetch and verify real-world data—anything from commodity prices to weather conditions—could be subject to national or regional data processing laws, such as GDPR in the EU or the CCPA in California. The decentralized nature of oracle networks often makes it impossible to enforce localized compliance across global node operators. If a node inadvertently handles sensitive data or triggers automated contracts tied to actions regulated in a specific country, the originating contributors could face unexpected regulatory enforcement.

Historically, government agencies have used broad interpretations of securities, money transmission, and consumer protection laws to clamp down on decentralized platforms. Precedents from enforcement actions against early DeFi protocols and token issuers suggest that regulators do not need centralized leadership to establish liability. Decentralized oracle builders—particularly those involved in governance or tokenomics design—should assume potential legal exposure, regardless of how distributed the system architecture might be.

Moreover, decentralized oracles pose systemic risks when they underpin synthetic assets, prediction markets, or derivatives. Should an oracle feed fail or be manipulated, the cascading impact on financial contracts could resemble traditional market manipulation in the eyes of regulators. Forward-looking jurisdictions may soon begin classifying oracle manipulation as a form of securities fraud or algorithmic price-fixing—both harshly prosecuted offenses.

Regulators may also categorize oracles as critical financial infrastructure if they consistently serve high-liquidity protocols. Mandatory audits, off-chain reporting disclosures, or operator licensing could become required in certain markets, especially where regulatory sandboxes are tightening. This transition from a “build first, ask later” model toward a compliance-first framework will demand significant adaptation from DAO-based oracle networks and their associated contributors.

These legal uncertainties intersect with fragmented local regulations, creating conflicting expectations—raising the odds of regulatory arbitrage while deterring institutional adoption. Oracle systems that double as governance token ecosystems, like Tellor Network, face heightened scrutiny as their tokens may be deemed financial instruments depending on how price data and voting rights are bundled.

This evolving compliance landscape sets the stage for Part 8—an in-depth analysis of the economic and financial consequences as decentralized oracles gain traction across blockchain-native and traditional markets.

Part 8 – Economic & Financial Implications

Economic and Financial Implications of Decentralized Oracles: Disruption, Incentives, and Systemic Exposure

The integration of decentralized oracles is reshaping financial dynamics in both DeFi and traditional markets—not just by enabling new products, but by introducing novel liquidity flows, investment structures, and unanticipated forms of risk.

One of the most immediate disruptions lies in the outsourcing of trust from centralized data providers to a freelance network of independently incentivized actors. For institutional investors, this opens new yield strategies—staking in oracle networks like Tellor or participating in collateral-backed data assurance systems. However, yield potential is tightly coupled to assumptions about uptime, network integrity, and dispute resolution—none of which are guaranteed in low-security oracle environments. Fragile economic assumptions can unravel swiftly when subject to sybil attacks or latency exploits.

On the buy-side, traders increasingly rely on oracles not merely for price feeds, but for real-world event triggers (sports, commodities settlement, weather derivatives). This creates asymmetric information advantages if certain teams have privileged visibility into the voting or dispute layers of oracle protocols. As these financial instruments become more algorithmically driven, compromised data sources don’t just cause bad trades—they trigger cascades of liquidations and smart contract events.

For builders, decentralized oracles lower the barrier to deploying real-world DeFi products. But with that comes an unsolved challenge: valuation of data itself. Developers must assess whether an oracle’s data quorum is economically credible. Is it backed by sufficient bonded stake? Is the governance prone to cartelization? Oracles such as Tellor offer participatory models, but design flaws around latency, miner incentives, and gas efficiency remain debated. A deeper look at these governance challenges can be found in Tellor TRB Navigating the Future of Blockchain Oracles.

The systemic implications become stark when viewing oracles as undercollateralized flashpoints. Unlike DeFi lending protocols that require collateral buffers, oracles expose the ecosystem to unbacked assurances priced into billions in TVL. Poor coordination between chains and validators even raises the prospect of fragmented consensus on data truth across ecosystems—a risk only magnified in multichain deployments.

Even speculative exposure is evolving. New financial primitives like data marketplaces, bonded truth-mining, and DAO-insured data feeds are surging—but these mechanisms remain largely untested at scale. Investors may be seduced by high APYs or governance perks while underestimating the long tail of correlated oracle failures.

These financial shifts are only part of the broader picture. Next, we turn our lens toward the societal and philosophical ramifications of decentralized oracles—how this architecture of trust could redefine notions of truth, consensus, and digital neutrality.

Part 9 – Social & Philosophical Implications

Decentralized Oracles and Market Disruption: A Realignment of Value and Exposure

The rise of decentralized oracles is not a secondary subplot in crypto's evolution—it is a quiet but imminent threat to entrenched data monopolies, a generator of new asset classes, and a vector for systemic financial risk.

Traditional financial institutions benefit from exclusive access to proprietary data through commercial data vendors—think Bloomberg Terminals. Decentralized oracle networks threaten this model by democratizing data provision, enabling anyone with verifiable sources and incentives to become a feed. Tokenized ecosystems like Tellor and API3 allow market participants—from independent analysts to sensor node operators—to monetize contributions to real-time data flows. This expands the addressable market but dilutes legacy control.

For traders and DeFi participants, decentralized oracles offer higher composability and arbitrage strategies that hinge on trustless, low-latency data inputs. From synthetic asset pricing to perpetuals, the integrity of inputs becomes a differentiator. Yet, with this opportunity comes exposure: if oracle networks are gamed—whether via sybil attacks or cartelized collusion—the resultant price feeds can induce cascading liquidations or falsely inflate asset values. As seen across earlier DeFi exploits, oracle vulnerabilities aren’t theoretical.

Institutional players may gain through strategic positioning in oracle token economies. But they’ll need to recalibrate risk models: oracle networks’ dependencies don’t behave like equities or bonds—they behave like asynchronous consensus-driven networks with persistent uptime pressures and unpredictable staking behavior. For those used to quarterly balance sheets, this unpredictability will either be a deterrent or a speculative play.

Protocol developers, meanwhile, must navigate an evolving incentive landscape. Do they bake oracle economics into their native token utility, or delegate data reliability to external providers via fee-sharing? Projects like Tellor have already been forced to rethink these paradigms under market pressure, as explored in https://bestdapps.com/blogs/news/tellor-trb-the-oracle-under-fire. The wrong design choice could make a promising dApp ecosystem too expensive to sustain or too brittle to attract liquidity.

And finally, regulators are watching—though often misunderstanding. Decentralized oracles blur the line between data provision and financial intermediation, exposing projects to new types of compliance headaches. If an oracle misfeeds inflation data to a stablecoin protocol, is that a pricing error or a misrepresentation of fact?

As for wider societal implications—autonomous data systems redefining truth and trust—that's a framework deserving its own layer. We'll examine that next.

Part 10 – Final Conclusions & Future Outlook

Final Conclusions & Future Outlook: Will Decentralized Oracles Define the Next Blockchain Epoch?

After dissecting the layered mechanics, governance structures, incentive models, and deployment challenges of decentralized oracles, one point becomes clear: their role is far from auxiliary. These infrastructures are now foundational to the validity, security, and reliability of on-chain data. Yet, the invisible nature of their function places them in a precarious position — under-utilized and under-scrutinized.

The best-case scenario envisions decentralized oracles maturing into modular, composable trust engines. They would integrate seamlessly into multi-chain ecosystems and L2 app chains, servicing DeFi, supply chains, IoT, and even decentralized social graphs. In this configuration, innovations such as zero-knowledge proofs and multi-party computation augment oracle data with provable integrity, eliminating reliance on a single point of failure. Protocols like Tellor have hinted at such trajectories, but the clock is ticking on their scalability and data diversity strategies (https://bestdapps.com/blogs/news/unlocking-tellor-the-future-of-decentralized-oracles).

The worst-case scenario, however, isn't a total collapse — it's mediocrity. If oracles remain opaque, poorly governed, or co-opted by centralized data gatekeepers, they will merely replicate the flaws of Web2 in a Web3 veneer. This would render critical dApps — from synthetic asset platforms to insurance protocols — vulnerable to oracle manipulation. Regulatory pressure could exacerbate these issues, tilting the balance toward "compliant" oracles that sacrifice decentralization for corporate partnerships and whitelist access.

Several unanswered questions remain central. Should oracle networks prioritize economic incentives or cryptographic guarantees? Can governance be truly decentralized when data providers oligopolize information flow? And how do we ensure oracle networks are secure without excessive token inflation or permissioned validator models?

Mainstream adoption will demand composability with cross-chain messaging protocols, non-financial applications, and standards for data interoperability. Without consensus on trust-minimized aggregation methods, censorship-resistant relays, and stake-slashing mechanisms, adoption will lag.

Real transformation hinges on user perception: when users care as much about who verifies their data as they do about who signs their transactions, oracle networks will step out from behind the curtain.

And so we’re left with an essential question: will decentralized oracles quietly lay the foundation for a more trustworthy blockchain ecosystem — or will they fade into obscurity, eclipsed by shinier innovations and forgotten like many protocol layers before them?

For readers interested in how geospatial inputs are shaping new oracle use cases, see https://bestdapps.com/blogs/news/xyo-network-pioneering-geospatial-data-in-blockchain.

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