The Problem It Solves

We're used to AI and online services learning about us—Spotify knows your music taste, TikTok curates content for you, and Amazon predicts your next purchase. But do you actually own that data? Your AI memories?

Right now, your behavior data is locked inside these platforms. If TikTok disappeared tomorrow, your AI memories would be lost. Worse, companies collect, sell, and profit from your data without your consent, and you never truly know who has access to it.

What This Changes

With our system, you own your AI memories. Instead of platforms harvesting it for free, you store it securely on decentralized storage and control access through smart contracts.

• 🔍 Transparency – Know exactly who accesses your data and why through an open, verifiable system.
• 💰 Monetization – Sell your insights directly to companies on your terms, cutting out the middlemen.
• 🔄 Portability – Take your preferences, AI history, and behavioral insights with you across platforms.
• 🔒 Security – Your data is encrypted, protected with decentralized keys, and cannot be exploited without your consent.
• 📊 AI Knowledge Ownership – Keep the data that AIs generate about you and add it to your profile, building your preferences over time. You decide which preferences can be shared and with whom.

How It Works

Marketers, AI services, and businesses already pay for user data—but now, they buy it from you.

• 🤖 An LLM can instantly tailor responses based on your self-owned knowledge base, making AI interactions smoother and more relevant.
• 📑 An insurance agent can autofill a quote using only what they need, purchasing access to specific data points you authorize.
• 🎵 A music app can instantly learn your preferences without tracking you—because you provide the data yourself instead of being passively monitored.

User Interaction and Data Flow

1️⃣ Account Creation

Users (or an AI agent) connect their Web3 wallet to the dApp, creating their account.

• The user enters optional basic information (e.g., age, hobbies, travel, food).
• Only a name is required—other data is added over time.

2️⃣ AI Behavior Profile Growth

As users interact with LLMs, music services, social media, shopping, or government sites, their profile updates automatically.

• Data is organized into JSON categories for controlled sharing.

3️⃣ Secure Storage & Encryption

• Data is stored on EthStorage but is unencrypted by default.
• Lit Protocol encrypts each category, ensuring privacy.

4️⃣ Granting Third-Party Access

1. 🔔 A third party requests data via the web app.
2. ✅ The user approves or denies the request.
3. 🔓 Approved data is decrypted with Lit Protocol and shared.
4. 🔄 The third party uses the data in their application.

5️⃣ Profile Updates After Interactions

• New insights from the interaction update the user’s profile.
• The updated data is re-encrypted and stored securely.
• Users can always view and manage their profile.

🔐 Full Control & Transparency

Users always know who accessed their data, what was shared, and how their profile evolves—ensuring true ownership of AI-driven personal data.

Project Architecture and Development Process

🏗️ Overview

This project enables user-controlled AI data ownership, using decentralized storage, encryption, and smart contracts. Instead of platforms passively collecting user data, users store their own AI-generated insights and control access through Web3 mechanisms.

⚙️ Core Functionality

1. User Profile & AI Behavior Data
   • Connects via Web3 wallet to create an account.
   • Profile grows dynamically as users interact with AI, music, social media, and government services.
2. Secure Storage & Encryption
   • EthStorage stores user data immutably.
   • Lit Protocol encrypts profile data, ensuring privacy.
3. Smart Contract Access Control
   • Users grant fine-grained permissions for data access.
   • Blockchain logs all interactions, ensuring transparency.
4. Permission-Based Data Sharing
   • Third parties request access via the web app.
   • Users approve, deny, or sell access based on need.
   • Decrypted data is shared via Lit Protocol.
5. Profile Updates After Interactions
   • AI-generated insights update the user’s profile.
   • Data is re-encrypted and stored securely.
   • Users always have access to their full data history.

🏛️ Architectural Components

• Frontend (React + Web3)
  • User authentication via MetaMask, etc.
  • Data management dashboard for approvals & permissions.
• Backend (Node.js + Smart Contracts)
  • Solidity smart contracts control access & payments.
  • Integration with EthStorage & Lit Protocol.
• Blockchain Layer (Ethereum + Smart Contracts)
  • Stores permissions and access history for transparency.

🔨 Development Process

1. Smart Contract Development – Solidity contracts for data access and monetization.
2. Storage & Encryption – Deploying EthStorage and Lit Protocol

Product Integrations

This project integrates key Web3 and AI services to ensure secure data storage, encrypted access control, and seamless user interactions. Below are the core APIs and services used and their roles:

🔑 Authentication & Wallet Integration

• MetaMask / WalletConnect – Enables users to authenticate and sign transactions using their Web3 wallets.
• Ethereum Blockchain – Hosts smart contracts for permission control, monetization, and audit logging.

🗄️ Decentralized Storage & Encryption

• EthStorage – Provides immutable, decentralized storage for user AI behavior profiles.
• Lit Protocol – Encrypts stored data and manages decryption keys for controlled access.

🤖 AI & Personalization

• ElizaOS – Manages AI interactions, processes user behavior data, and refines AI behavior profiles.
  • Supports plugin-based integrations with services like WhatsApp, Discord, X, and other communication platforms.

🔗 Smart Contracts & Access Control

• Solidity Smart Contracts – Governs data access, payments, and sharing approvals on Ethereum.

💰 Monetization & Payments

• Ethereum / Layer 2 Solutions – Supports fast, low-cost transactions for buying/selling AI data access.

📡 Third-Party Access & Permissions

• REST API – Provides a developer-friendly interface for third parties requesting data.

By combining ElizaOS, blockchain, decentralized storage, and smart contract access control, this project gives users full ownership over their AI-driven data while enabling secure, monetized sharing. 🚀

Comparison with Similar Projects

🔹 Your Project

• Focus: AI behavior data ownership & monetization.
• Data Ownership: Users fully control and sell their AI-generated data.
• Storage: EthStorage for decentralized storage.
• Encryption: Lit Protocol for secure, permission-based access.
• Monetization: Smart contract-based AI data sales.
• AI Integration: ElizaOS with plugin support (WhatsApp, Discord, etc.).
• Transparency: Users track who accessed their data.

🔹 Ocean Protocol

• Focus: Open data exchange for businesses & researchers.
• Data Ownership: Data providers share datasets but mostly for open use.
• Storage: Uses IPFS & blockchain.
• Encryption: Optional, but not a focus.
• Monetization: Uses data tokens for dataset trading.

🔹 AIOZ Network

• Focus: Decentralized AI dataset & model hosting.
• Data Ownership: Users sell datasets & AI models in a network.
• Storage: Uses AIOZ blockchain & decentralized nodes.
• Encryption: Users manage access manually.
• Monetization: AI developers license & sell models.
• AI Integration: Focuses on AI model hosting

🔹 DECORAIT

• Focus: AI training opt-in/opt-out registry for content creators.
• Data Ownership: Creators control how AI models use their work.
• Storage: Blockchain-based metadata registry.
• Encryption: No encryption, just tracking.
• Monetization: Royalties for AI training contributions.
• AI Integration: Manages content rights, not personal AI behavior.

🚀 Key Differentiators

✅ AI-Specific Data Ownership – Unlike AIOZ, your project manages AI-generated personal behavior data.
✅ End-to-End encryption

Trade-offs and Shortcuts While Building

⏳ Access Permissions for Agents

We made a trade-off by simplifying the access control system for AI agents. Instead of a granular permission structure, we opted for basic approval mechanisms, allowing users to grant or deny access to entire block of data. Future improvements include fine-grained permissions per agent

🔍 Identity System Limitations

A more robust identity verification system using verifiable hashes was planned but not implemented due to time constraints. This would have ensured cryptographic proof of identity, making AI behavior data more trustworthy and portable. Future versions will explore DID (Decentralized Identity) integration.

🧪 AI Testing & Group Interaction

We couldn’t fully test AI behavior in group scenarios. While AI agents function well individually, multi-agent interactions (e.g., travel assistant working with real estate assistant) remain untested. Further testing will improve collaborative AI decision-making.

🛒 Marketplace for Data Monetization

The initial vision included a marketplace where users could sell or license their AI-generated data to businesses or AI systems. We didn’t have time to implement this, but a future version could include smart contract-based transactions for direct user-to-business AI data exchanges.

🔄 AI Writing Back User Behavior Data

Currently, AI agents can read user preferences but do not write back new behaviors. Ideally, AI should update a user's stored preferences dynamically based on real interactions, ensuring profiles evolve over time. Future iterations will allow AI agents to write back behavior updates securely, while maintaining user oversight and edit rights.