Technical Details and Use Cases

zkos.ai

1.Core Features

🔍 Behavioral Analysis

Analyzes historical on-chain activity like lending, trading, and staking to generate a normalized reputation score (0–1000).

🔁 Cross-Chain Verification

Reputation scores are synced across supported blockchains to provide a consistent, verifiable identity layer.

🧱 Sybil Resistance

Patterns in wallet activity help filter real users from bots and malicious actors.

⚠️ Risk Assessment

Lending protocols can dynamically adjust terms (e.g., LTV, rates) based on a user’s wallet reputation.

🎖️ Loyalty Recognition

Protocols can reward long-term, high-reputation users with premium access, perks, or better terms.

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2.Use Cases

🏦 Lending Markets

• Adjust collateral requirements dynamically

• Reward high-reputation users with better rates

🎨 NFT Projects

• Block bot accounts from public mints

• Identify real collectors for whitelists and rewards

📈 DEX Platforms

• Set leverage limits or fee tiers by trading history

• Enhance user segmentation based on wallet behavior

🎁 Airdrops

• Prevent Sybil farming

• Focus on wallets with authentic engagement

🔐 Gated Protocol Access

• Enable features based on verifiable wallet trust

• Build ecosystem tiers with trust-based criteria

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3.Architecture Overview

🔄 Data Collection

• Event Collector monitors transactions across DeFi protocols (lending, trading, staking)

• Data is indexed by wallet address → network → protocol

• Updates every 6 hours

• Uses zkTLS for integrating off-chain credentials where possible

⚙️ Score Computation

• Execution Service processes wallet data using distributed workers on Ethereum

• AI-based behavioral models assign reputation scores (0–1000)

• Each score is cryptographically signed and stored in RocksDB

• A Merkle tree is updated for fast proof generation and verification

🧑‍⚖️ Operator Network

• Validators stake ETH via EigenLayer to participate

• New score batches are verified via random sampling and consensus

• Requires 2/3 majority approval to finalize and publish scores

• Secured by over $1B in restaked ETH

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4.Onchain Storage & Proof System

• Smart contracts on each chain store the verified Merkle root

• Roots updated every 6 hours post-operator consensus

• Only root hashes stored on-chain → low gas costs

• Scores stored off-chain but can be independently verified via Merkle proofs

• ScoreRegistryReceiver handles incoming root updates via LayerZero

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5.Cross-Chain Sync

• Once scores are verified, a central attestation center commits the Merkle root to each blockchain

• Uses LayerZero messaging to coordinate updates

• Each chain has a Score Registry contract to maintain the latest state

• Ensures every protocol accesses consistent, up-to-date data

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6.Integration Guide

🛠️ API Access (AVS Interface)

Protocols can access wallet scores using the AVS API:

bashCopyEditGET /score/{wallet_address}

Each response includes:

• Wallet’s normalized score

• Timestamp of last update

• Merkle proof for on-chain validation

🔐 On-chain Verification Flow

1. Fetch score + Merkle proof from zkOS API

2. Submit to the smart contract

3. Contract verifies proof using latest stored Merkle root

4. Proceed with logic (access, rewards, rate adjustment, etc.)

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7.Getting Started

Coming soon: SDKs and developer resources for Solidity, Rust, and TypeScript to make integrating zkOS easy.