DEMO LINKS\\nDevpost: https://devpost.com/software/seahorse-social\\nDemo Video: https://seahorse-phi.vercel.app/\\nGitHub: https://github.com/KonferCA/Seahorse\\n\\nWhat it does\\nSeahorse is a decentralized wellness AI with privacy as our core ideology. Here is how it works:\\n\\nDecentralization of Data Sources\\nPrivacy and Control: Reduces dependency on centralized servers, allowing users to retain control over personal data like emails, calendars, and documents.\\nEnhanced Security: Decentralized nodes increase resilience and data security.\\n\\nOpen-Source Language Model Integration\\nTransparency: Enables customizable, transparent models that avoid reliance on third-party, black-box solutions.\\nPrivacy-By-Design: Aligns with privacy-first principles, ensuring model processing occurs securely on-device.\\n\\nBlockchain-Based Compensation with NEAR Protocol\\nAutomated Fair Compensation: Data providers receive payment based on data relevance and usage, fostering transparency and trust.\\nReal-Time Accountability: Tracks data interactions on-chain, ensuring tamper-proof, accountable compensation.\\n\\nUser Privacy and Data Ownership\\nAccess Control: Users retain granular control over shared data (e.g., email, calendar).\\nOn-Device Processing: Minimizes exposure to external systems, enhancing compliance with data privacy regulations.\\nEmpowerment Through Privacy: Privacy-by-design principles encourage user trust by ensuring data ownership and control.\\n\\nEthical AI Development\\nFair Compensation and Data Ownership: Sets a standard for ethical AI by respecting data ownership and fairly compensating providers.\\nUser Privacy and Functionality: Balances AI functionality with strict data privacy, promoting responsible AI use.\\nCheck it out yourself if you don\\\'t believe us! https://github.com/KonferCA/Seahorse\\n\\nScalability and Flexibility\\nModular Design: Accommodates various data sources and modalities, including multimodal capabilities.\\nScalability: Designed to scale with more extensive datasets and data types, increasing versatility.\\n\\nFoundation for Future Innovations\\nDecentralized AI Proof of Concept: Paves the way for future decentralized AI applications centered around data privacy and ownership.\\nOpen Infrastructure Development: Provides a foundation for projects focused on user privacy, data control, and decentralized compute.\\n\\nHow we built it\\nA decentralized Retrieval-Augmented Generation (RAG) system with a blockchain-based compensation model that prioritizes data ownership and privacy. The system processes personal data, such as Google Calendar entries, emails, and transcriptions, entirely on-device using advanced similarity search with all-MiniLM-L6-v2 embeddings. A secure, wallet-based routing system enables two users to exchange decryption keys, allowing access to shared calendar and event data stored encrypted on NEAR Protocol\\u{2019}s blockchain. Compensation for data providers is managed through NEAR smart contracts, which distribute payments based on data relevance scores. Initially centralized for simplicity, the routing system is designed with future decentralization in mind.\\n\\nThis project aims to set new standards in ethical AI by combining privacy-focused, decentralized data processing with a fair, automated compensation structure for data contributors.\\n\\nOn-Device System\\nOn-Device RAG System: An entirely on-device Retrieval-Augmented Generation (RAG) system pulls relevant information from diverse sources.\\nData Sources: Includes Google Calendar, Gmail emails, uploaded documents, voice transcriptions, and more.\\nVector Embeddings: Uses all-MiniLM-L6-v2 model to map text into a dense vector space for similarity searches.\\nFlexibility: Designed for plug-and-play functionality to accommodate new information as needed.\\nResponse Generation: Uses WebLLM to run Phi 3.5 Vision Instruct on-device for responses, pulling only relevant data.\\n\\nSmart Contract Integration: Relevancy scores and data usage are logged for fair compensation calculation. This information is sent to NEAR Protocol, which calculates and distributes payments based on data relevance.\\nVoice Transcription: Uses Web Speech API for on-device transcription, storing notes locally for user retrieval and RAG system reference.\\nSmart Contract System\\nData Management: Data providers manage their information directly on NEAR\\u{2019}s blockchain.\\nDirect Updates: Providers can update, add, or remove data on the blockchain, formatted specifically for the RAG system.\\nCompensation Calculation: Smart contract computes compensation based on data type and relevance scores, immediately distributing NEAR tokens to providers\\u{2019} wallets.\\nEncrypted User Data Storage: Stores user information (calendar, documents, etc.) in encrypted form. Decryption occurs solely on-device, enabling private data sharing within the RAG system.\\nShared Events: Includes multi-user interactions like shared calendar events, enabling better decision-making between parties.\\n\\nSecure Routing System for Key Exchange\\nAllows two users to establish a secure key exchange to decrypt calendar or event data stored on the NEAR blockchain.\\n\\nMechanism:\\n- NEAR Wallet-Based Identification: Each user is identified by their NEAR wallet, establishing a unique route for connection.\\n- Key Exchange: Users initiate a key exchange over a secure, temporary routing channel that connects their wallets. Once exchanged, each user holds a key to access shared calendar or event data.\\n- Encrypted Storage and Access: After the key exchange, calendar or event data stored on-chain remains encrypted. Only the involved users, who possess the corresponding keys, can decrypt the shared data on-device.\\n\\nCentralized Routing with Future Decentralization Potential:\\n- Current Setup: The routing system is centrally managed to streamline initial development, with key exchanges handled through secure server channels linked to NEAR wallets.\\n- Decentralization Plan: In future iterations, the routing can transition to decentralized protocols (e.g., peer-to-peer or DHT-based systems), allowing users to securely exchange keys without centralized routing.

1st Place Winning project at the REDACTED Hackathon City node Waterloo! 

With Seahorse, we wanted to combat loneliness and enhance mental health through an AI-powered wellness engine that provides personalized support and connects users with a real-life community of like-minded individuals.\\n\\nThis was accomplished by creating online accountability through an AI wellness recommendation engine. This platform guides users in self-care while connecting them in real life to a supportive community of like-minded individuals, fostering in-person accountability and growth.

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