Zion
Empowering Text-Based IPs (Such as cover letterswith Blockchain to Create a Thriving Marketplace for Digital Ownership and Monetization
Created on 12th April 2025
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Zion
Empowering Text-Based IPs (Such as cover letterswith Blockchain to Create a Thriving Marketplace for Digital Ownership and Monetization
The problem Zion solves
Zion's Solution to Text-Based IP Challenges
Zion addresses four key challenges in the text-based IP ecosystem, focusing on documents like resumes and cover letters that contain valuable personal information:
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Privacy-Preserving Value Exchange
Resumes often include sensitive personal details, making public sharing risky. Zion provides a secure framework for tokenizing these documents, allowing AI systems to utilize valuable components without exposing private data. This enables monetization while maintaining privacy. -
Monetization of Personal Content
Resumes and cover letters require significant intellectual effort but lack monetization opportunities. Zion transforms these documents into blockchain-based digital assets, allowing creators to earn compensation when their work influences others, fostering a sustainable reward system. -
Transparent Attribution System
Current platforms fail to track reference relationships between text documents. Zion uses Story Protocol to record these interactions on-chain, ensuring contributors receive proper credit and fair compensation for their influence. -
Combining Creativity with Personal Value
While creative text IPs like web novels have seen tokenization efforts, personal documents remain underutilized in blockchain ecosystems. Zion bridges this gap by enabling users to share and monetize personal content responsibly, benefiting from their intellectual contributions while protecting privacy.
Challenges we ran into
During development, we encountered several significant challenges:
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Balancing Privacy and Transparency: Designing a system that respects sensitive personal data while maintaining blockchain transparency was challenging. We implemented tokenization methods to separate private data from structural elements that AI systems can utilize.
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Text Similarity Assessment: Unlike visual media, determining reference relationships between text documents required robust algorithms to differentiate inspiration from coincidence. We used Pinecone Vector DB to establish meaningful thresholds for attribution.
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Smart Contract Complexity: Developing reward distribution mechanisms through Story Protocol’s License Module required intricate logic to account for varying degrees of contribution across multiple documents. We implemented weighted contribution models to ensure fairness.
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Marketplace Integration: Building an intuitive user experience for an e-commerce-like marketplace was challenging due to blockchain complexity. We simplified this by integrating Privy SDK for seamless wallet creation and providing a dashboard that abstracts technical details.
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Technical hurdles: During the process of registering derivatives, we encountered difficulties when trying to trace issues because the documentation and sample code omitted the critical step of transferring License Token authorization to Story's smart contract. We resolved this problem by implementing the authorization transfer functionality ourselves.
Tracks Applied (2)
General Track
Agent on Story
Story
