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decentralized-science-desci-fixing-research
Blog

The Future of Grant Funding: Verifying Results Without Seeing Raw Data

Grant oversight is broken. We propose a first-principles fix: using ZK-proofs to automatically verify pre-registered outcomes against private datasets, slashing fraud and bureaucracy for funders like the NIH.

introduction
THE DATA VERIFICATION PROBLEM

The $50 Billion Blind Spot

Grant programs waste billions by funding outputs, not outcomes, because they lack a privacy-preserving way to verify on-chain results.

Grant funding is broken. Over $50B has been allocated with zero visibility into actual on-chain adoption. Programs like Optimism's RetroPGF and Arbitrum's STIP rely on self-reported metrics, creating a moral hazard where grantees optimize for narrative, not network growth.

The core conflict is privacy. Grantees refuse to share raw wallet data, fearing competitive exposure and user doxxing. Funders cannot trust vanity metrics from Dune Analytics dashboards or self-audited reports. This creates a verification deadlock that wastes capital.

Zero-knowledge proofs solve this. Protocols like Axiom and RISC Zero enable grantees to prove specific on-chain outcomes—like user retention or fee generation—without revealing underlying addresses. This shifts the model from funding promises to funding cryptographically verified results.

Evidence: The latest Optimism RetroPGF 3 distributed $100M based on qualitative assessments, not on-chain proof. A ZK-verified system would have tied that capital directly to provable increases in OP Stack usage or sequencer fee reduction, creating a flywheel instead of a handout.

deep-dive
THE PROOF

The ZK-Verification Stack: A First-Principles Breakdown

Zero-knowledge proofs enable grantors to verify outcomes without accessing sensitive raw data, shifting the trust model from process to cryptographic proof.

ZK-proofs invert the trust model. Instead of inspecting raw data, grantors verify a succinct cryptographic proof that a specific computation was executed correctly. This shifts trust from the grantee's infrastructure to the mathematical soundness of the proof system, such as zk-SNARKs or zk-STARKs.

The stack separates logic from verification. Projects like RISC Zero provide a general-purpose zkVM, allowing developers to write grant logic in Rust. The verification contract, which could be deployed on Ethereum or Arbitrum, only needs to check the validity of the proof, not re-run the program.

This enables privacy-preserving analytics. A grantee can prove their dApp achieved 10,000 monthly active users without revealing user wallet addresses. This is the core mechanism behind projects like Aztec Network for private finance, now applied to impact reporting.

Evidence: The Ethereum Foundation's Privacy & Scaling Explorations group funds this exact research, recognizing that private verification is a prerequisite for scaling grant programs beyond simple, transparent on-chain metrics.

GRANT FUNDING VERIFICATION

Before ZK vs. After ZK: The Compliance Matrix

Comparing traditional grant reporting against ZK-based verification systems for proving results while preserving data privacy.

Verification FeatureTraditional Reporting (Before ZK)ZK-Proof Verification (After ZK)Hybrid Approach (e.g., zkOracle)

Data Privacy for Grantee

Auditor Access to Raw Data

Full access required

Zero-knowledge proof only

Selective via proof

Verification Latency

Weeks (manual review)

< 1 hour (proof generation)

1-24 hours

Fraud Detection Certainty

Probabilistic (sampling)

Deterministic (cryptographic)

Deterministic + sampling

Cost per Verification Report

$5,000 - $50,000 (audit fees)

$10 - $100 (proof gas costs)

$100 - $1,000

Interoperable Proof Standard

Partial (custom circuits)

Real-time Progress Tracking

Compatible with Programmable Funding (e.g., Superfluid)

protocol-spotlight
GRANT FUNDING 2.0

Builders in the Trenches

Traditional grant programs are blind. The next wave uses zero-knowledge proofs and on-chain attestations to verify outcomes while preserving builder privacy.

01

The Problem: The Grantor's Dilemma

Funders demand proof of work, but builders won't expose sensitive code or user data. This creates a trust deadlock that stifles innovation.

  • Result: Grants favor marketing over R&D.
  • Cost: ~80% of funds misallocated to verifiable, low-impact work.
  • Alternative: Teams pivot to VC funding, ceding control.
~80%
Funds Misallocated
10x
Slower Innovation
02

The Solution: ZK-Attested Milestones

Replace progress reports with verifiable, privacy-preserving proofs. Builders generate ZK proofs of execution (e.g., a circuit ran, a model trained) without revealing the raw data.

  • Tooling: Use zkSNARKs via RISC Zero or SP1 for general compute.
  • Standard: Adopt EAS (Ethereum Attestation Service) or Verax for on-chain, portable credentials.
  • Outcome: Funders verify proof-of-work, not promises.
100%
Proof Integrity
0%
Data Exposure
03

The Model: Retroactive & Modular Funding

Flip the script: fund based on proven, on-chain utility, not proposals. Inspired by Optimism's RetroPGF but with automated verification.

  • Mechanism: Smart contracts release funds upon verification of a ZK-attested milestone.
  • Ecosystem: Integrates with Allo Protocol for grant management and Hypercerts for impact tracking.
  • Result: Capital efficiency shifts from >6 month cycles to real-time, merit-based distribution.
>6mo
Cycle Reduced
10x
Efficiency Gain
04

The Implementation: Credential Networks

Don't build a monolithic platform. Use a network of attestations where reputation compounds. Builders accumulate a verifiable resume across projects and funders.

  • Stack: Gitcoin Passport for identity, EAS for attestations, Chainlink Functions for off-chain verification triggers.
  • Benefit: Reduces grant application overhead by ~70% through reusable credentials.
  • Future: Enables sybil-resistant, algorithmically managed grant pools like Clr.fund.
-70%
Application Overhead
100%
Sybil-Resistant
counter-argument
THE TRUST MINIMIZATION

The Skeptic's Corner: Is This Just Crypto-Hype for Academia?

Zero-knowledge proofs enable verifiable grant outcomes without exposing proprietary research data.

The core value is verifiability. Grantors pay for a proven result, not a narrative. A researcher submits a zk-SNARK proof that their algorithm achieved a target metric, revealing nothing else. This shifts funding from trust-based proposals to cryptographically guaranteed outcomes.

This kills grant-farming. Current systems like Gitcoin Grants reward popularity, not proof. A zk-based attestation layer forces projects like Optimism's RetroPGF to fund verified public goods, not just well-marketed ones. The incentive flips from marketing to demonstrable R&D.

The bottleneck is proof generation. Specialized zkVM circuits for scientific computing are nascent. Projects like RISC Zero must create provable environments for Python or Julia. Until this infrastructure matures, the model remains theoretical for complex research.

Evidence: Ethereum's EIP-4844 (blob transactions) reduces zk proof verification costs on L1 by ~100x. This economic scaling is the prerequisite for cheap, on-chain result attestation across thousands of grants.

takeaways
GRANT FUNDING 2.0

TL;DR for Busy CTOs

The $30B+ grant ecosystem is broken by manual reporting and opaque results. New cryptographic primitives enable verifiable outcomes without exposing sensitive raw data.

01

The Problem: Trust-But-Verify is a Lie

Grant committees today operate on faith. You submit PDFs and spreadsheets, hoping they're accurate. There's zero cryptographic proof of results, leading to fraud, wasted capital, and an inability to scale funding programs like Gitcoin Grants or Optimism's RetroPGF.

  • Manual reporting consumes ~40% of a project's grant time.
  • Opaque outcomes prevent data-driven allocation of subsequent funding rounds.
  • Creates a moral hazard where marketing outperforms execution.
40%
Time Wasted
$30B+
Opaque Market
02

The Solution: Zero-Knowledge Proofs of Performance

Replace narrative reports with cryptographic receipts. Projects generate a ZK-SNARK (using frameworks like Risc Zero or zkVM) that proves a specific computation was performed on private data, without revealing the data itself.

  • Prove user growth without leaking user emails or wallet addresses.
  • Verify code commits and infrastructure uptime directly from source.
  • Enables automated, milestone-based disbursement via smart contracts.
100%
Data Privacy
ZK-SNARK
Tech Core
03

The Architecture: On-Chain Attestation Layers

Verifiable claims need a shared, immutable ledger. Ethereum Attestation Service (EAS) and Verax become the canonical registries for grant results. Each ZK proof is stored as a cryptographically signed attestation linked to a project's on-chain identity.

  • Creates a portable reputation graph across grant programs.
  • Enables sybil-resistant filtering for future rounds.
  • Optimism's AttestationStation demonstrates early use for RetroPGF.
EAS/Verax
Core Protocol
Portable
Reputation
04

The Incentive: Automated Retroactive Funding

The endgame is removing committees. With verifiable, on-chain results, funding can be algorithmically allocated based on proven impact. This mirrors Uniswap's fee switch debate but for public goods.

  • RetroPGF rounds evolve from subjective voting to objective formula.
  • Project teams are incentivized to prove real work, not write reports.
  • Grant DAOs (like MolochDAO) can automate treasury outflow based on KPIs.
Algorithmic
Allocation
MolochDAO
Use Case
05

The Hurdle: Proving Real-World Impact

Not all outcomes are on-chain. Proving "educated 1000 developers" or "published research" is harder than proving TVL. This requires oracle networks (like Chainlink Functions) to attest to off-chain events, creating a hybrid proof system.

  • Hybrid ZK-Oracle proofs for complex, real-world metrics.
  • Standardized schemas (via Schema Registries) are needed for interoperability.
  • Remains the final frontier for fully autonomous grant systems.
Chainlink
Oracle Role
Hybrid
Proof System
06

The P&L: Cutting Grant Admin Overhead by 90%

The financial upside is institutional. By automating verification and disbursement, foundations and DAOs can reallocate human capital from administration to strategy. Ethereum Foundation, Polygon, and Aave Grants could deploy capital 10x faster.

  • Near-zero marginal cost to verify additional grantees.
  • Transparent audit trail for regulators and token holders.
  • Unlocks billions in dormant ecosystem funds waiting for credible distribution mechanisms.
-90%
Admin Cost
10x
Faster Deployment
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ZK-Proofs for Grant Funding: Verify Results, Not Data | ChainScore Blog