The Future of Data Markets: Selling Proofs, Not Raw Data

Raw data feeds are expensive to source and expose protocols to manipulation risks like flash loan attacks. The value is in the verifiable attestation, not the bytes themselves.\n- Eliminates trust assumptions in data providers\n- Shifts cost model from continuous streaming to on-demand proof generation\n- Enables new financial primitives like proof-of-reserves and MEV-proof pricing

A programmable zkOracle network that generates ZK proofs for any off-chain computation, turning APIs into verifiable on-chain states. This is the intent-based architecture for data.\n- Proves historical states (e.g., Uniswap V3 TWAP) and real-time events\n- Native integration with rollups like zkSync and Scroll for synchronous proofs\n- Developer primitives for building autonomous, logic-driven smart contracts

A new economic layer where specialized provers compete to generate the cheapest, fastest ZK proofs for specific data computations (e.g., FX rates, sports scores).\n- Creates a proof marketplace similar to EigenLayer for AVS or Gelato for automation\n- Monetizes proprietary algorithms without revealing the underlying data\n- Drives down costs through prover competition and hardware specialization (GPUs/ASICs)

Inspired by intent-based bridges like Across and UniswapX, future oracles will separate data sourcing (any API) from attestation (ZK proof network). This breaks vendor lock-in.\n- Data sourcing becomes commoditized; proof security is the differentiator\n- Enables permissionless data feeds from any public API\n- Interoperability layer for proofs, similar to LayerZero's omnichain vision

ZK proofs enable the sale of verifiable insights (e.g., "credit score > 700") without exposing the underlying private data. This unlocks DeFi for private data.\n- Complies with regulations like GDPR by design\n- Enables private on-chain identity and undercollateralized lending\n- Creates a market for enterprise data (e.g., supply chain, IoT) without leakage

With verifiable off-chain computation, smart contracts can react to and act upon any real-world event without trusted intermediaries. This is the final piece for full decentralization.\n- Turns oracles into co-processors for limitless contract logic\n- Eliminates oracle manipulation as an attack vector\n- Unlocks AI-powered agents with provable execution traces

Transforms Ethereum's security into a reusable commodity. Projects can rent pooled cryptoeconomic security to launch new data availability layers or light clients.

• Key Benefit: Decouples security from consensus, enabling ~$15B+ in restaked capital to secure new protocols.
• Key Benefit: Drives down costs for rollups via EigenDA, offering data availability at ~90% lower cost than calldata.

Proves arbitrary on-chain history and state for smart contracts, enabling trust-minimized data consumption.

• Key Benefit: Contracts can compute over entire chain histories (e.g., TWAPs, user credentials) verified by ZK proofs.
• Key Benefit: Moves heavy computation off-chain, reducing gas costs for complex queries by 10-100x versus on-chain execution.

Generalizes the oracle model with zkGraphs, allowing developers to define and prove any off-chain logic for on-chain use.

• Key Benefit: Enables verifiable DeFi risk engines, on-chain AI inference, and real-world data triggers with cryptographic guarantees.
• Key Benefit: Eliminates oracle extractable value (OEV) by providing proofs, not just data, making systems like Chainlink and Pyth verifiable.

Legacy oracles like Chainlink provide data but not proof of correct execution, creating centralization risks and value leakage.

• Key Flaw: Oracle Extractable Value (OEV) allows MEV searchers to front-run price updates, siphoning millions annually from DeFi.
• Key Flaw: Data consumers must trust the operator's honesty, not cryptographic verification, creating a systemic weak link.

The end-state is a unified layer where any data or computation can be cheaply proven and consumed across chains.

• Key Vision: EigenLayer secures light clients, zkOracles prove data integrity, and co-processors enable complex logic, creating a composable truth layer.
• Key Vision: Data markets shift from selling raw feeds to selling verifiable attestations, with pricing based on proof generation cost, not data monopoly.

Provides a decentralized sequencing layer for rollups, turning transaction ordering into a verifiable, time-stamped data stream.

• Key Benefit: Rollups get censorship-resistant ordering and shared liquidity across ecosystems like Arbitrum and Optimism.
• Key Benefit: The sequence data is a high-fidelity feed for MEV analysis, cross-chain arbitrage, and intent-based systems like UniswapX.

Data markets require trusted attestations about the real world. Proofs are only as good as their inputs. A corrupted or lazy oracle feeding a ZK-proof system produces cryptographically verified garbage.

• Provenance Gap: Who attests to the initial data source? Chainlink and Pyth still centralize this trust.
• Liveness Risk: A proof of data unavailability is computationally intensive, creating new attack vectors.
• Cost Proliferation: Every attestation layer adds latency and cost, negating efficiency gains.

Proof systems (e.g., RISC Zero, Succinct) are not commodities. Each has unique circuits, proving backends, and trust assumptions.

• Protocol Capture: A market built on one prover stack inherits its bugs, costs, and governance.
• Fragmented Liquidity: Data priced in proof-hours on Network A is incompatible with Network B, defeating composability.
• Centralizing Force: The entity controlling the most efficient prover infrastructure becomes a de facto rent-extractor, mirroring AWS in web2.

Regulators target data and its use, not the cryptographic wrapper. Selling a 'proof of KYC compliance' doesn't absolve the underlying data handler of liability.

• Jurisdictional Arbitrage: Is the legal entity the data source, the prover, or the marketplace? All become targets.
• Privacy Illusion: Zero-Knowledge proofs protect specific data points, but the act of requesting a proof (e.g., a credit score) reveals intent and metadata, creating new compliance surfaces.
• Kill Switch Risk: A regulator can compel a prover to halt proofs for a specific class of data, bricking entire market applications.

Users think in data, not proofs. The mental and financial overhead of managing proof credits, gas for verification, and stake slashing is prohibitive for mainstream adoption.

• Hidden Costs: The end-user sees a data price, but pays: data cost + proof generation fee + verification gas + oracle fee.
• Staking Barriers: To be a reputable data seller, you must stake capital. This excludes long-tail, high-value data sources.
• Settlement Fragmentation: Proofs may settle on Ethereum, but data is used on Solana or an L2, requiring cross-chain asset bridges like LayerZero or Wormhole, adding another failure point.