🔄 CONSENSUS & BLOCKCHAIN

Provably Fair Consensus

ZPL brings mathematical fairness to distributed voting, DAO governance, and blockchain randomness. Every consensus has a verifiable AIN score — auditable on-chain.

Try Vote Demo View Code

Live Demo

Distributed Vote Consensus Simulator

Add voters with different biases and see how ZPL produces a mathematically fair consensus vs simple majority.

Voters (click to randomize bias)

Simple Average

0.74

biased toward majority

ZPL Consensus

0.51

✓ ZPL CERTIFIED

AIN Score: 0.93 — ZPL corrected 5 biased voters to equilibrium

The Whale Problem

In standard DAO voting — a whale with 40% stake can swing any vote their direction regardless of community sentiment

Simple majority — mathematically amplifies the bias of large stakeholders

Result — DAOs are effectively controlled by their top 5-10 holders

ZPL Solution

Weight-independent correction — ZPL normalizes the vote distribution regardless of stake weight

Mathematical proof — AIN score is on-chain verifiable, not just a claim

Result — community consensus reflects actual sentiment, not whale preference

Applications

Where ZPL Powers Blockchain

🏛️

DAO Governance

Whale-resistant voting. ZPL normalizes vote weight so large holders can't unilaterally control governance outcomes.

Anti-whale correction

📜

Smart Contract Randomness

On-chain randomness from ZPL oracle. AIN score is stored on-chain as proof of fairness for any contract requiring random outcomes.

Verifiable on-chain

⚖️

Dispute Resolution

Multi-sig arbitration with neutral tie-breaking. ZPL provides a mathematically neutral third opinion when arbitrators are split.

Neutral arbitration

🎰

Provably Fair Gaming

On-chain games need verifiable randomness. ZPL AIN score proves each game outcome was generated fairly before and after the fact.

AIN audit trail

🗳️

Quadratic Voting

Combine ZPL with quadratic voting for double-layered fairness — diminishing returns on large votes + equilibrium correction.

Dual fairness layer

🔗

Cross-Chain Consensus

When multiple chains need to agree on a shared state, ZPL provides a neutral reference point immune to any single chain's bias.

Chain-agnostic

Integration

ZPL Consensus in Code

// JavaScript — ZPL DAO vote aggregation async function zplConsensus(votes: number[]) { // votes = array of 0.0-1.0 values from each voter const avgBias = votes.reduce((a, b) => a + b, 0) / votes.length; const res = await fetch('https://zpl-backend.onrender.com/compute', { method: 'POST', headers: { 'X-Api-Key': 'zpl_your_key' }, body: JSON.stringify({ bias: avgBias, N: 9, samples: 1000 }) }); const data = await res.json(); return { simple_average: avgBias, // biased zpl_consensus: data.bias_output, // corrected to ~0.5 ain_score: data.ain_score, // on-chain proof certified: data.zpl_certified // store this on-chain }; }

PRICING

Simple, Transparent Pricing

Start free. Scale as your consensus infrastructure grows.

PRO

$29/month

35,000 compute calls/month

✓ POST /consensus endpoint

✓ Up to 1,000 nodes per vote

✓ 3 API keys