DataBarista
{"title": "DataBarista", "logoImg": "bafkreiaqmicidyepwmcwpkh65agojbri3jyxj2rpniai5is2lbcnco6jvq", "website": "https://databarista.ai", "bannerImg": "bafkreieyhntiubnc75rrudmbmlijsqwwvwwh63ixhn43wunycjxsuvdzne", "createdAt": 1741854119811, "userGithub": "amirmabhout", "credentials": {}, "description": "# I'm that Barista who remembers your stories & might just know someone you should meet!\n\n## **Problem**  \nTraditional networking—whether in-person or online—often falls short of delivering meaningful, tailored connections.  \n\n- In physical meetups, people often miss important details about one another, leading to missed opportunities and shallow interactions.  \n- Online, generic platforms spam users with attention-grabbing and irrelevant messages.  \n\n## **Meet DataBarista**  \n\nDataBarista tackles these challenges by building its own network—a community knowledge graph that unites private profiles with public, yet anonymous, intents.  \n\n### **How it Works**  \n![HowItWorks](https://devfolio-prod.s3.ap-south-1.amazonaws.com/hackathons/f8ebb5924ab74123bbd7088731ca9ab8/projects/59c25eb259ab46d48da3144b5aad9739/a56389ce-92f1-4d94-a6f6-06aa6fd39c55.jpeg)\n\n#### **1. Dual-Layer Knowledge Graph**  \nDataBarista’s network comprises two interconnected layers:  \n\n- **Private Profiles**: Privately stored user data in an edge node—including personal background, project details, and sensitive information—accessible only to DataBarista.  \n- **Public Intents**: Anonymized summaries of users’ professional goals and project challenges that remain verifiable and discoverable by the community public on DKG.  \n\n#### **2. Semantic Matchmaking**  \nThe matchmaking process is a two-step system:  \n\n1. **Rule-Based Filtering**:  \n   - Using SPARQL queries, the system scans the decentralized knowledge graph to retrieve candidate profiles that align with the user’s expertise, project domain, and desired connections.  \n\n2. **LLM-Driven Reasoning**:  \n   - A reasoning layer then leverages large language models to analyze these candidates semantically, ensuring that the selected match offers mutual benefits rather than a one-sided connection.  \n\n#### **3. Grassroot dataDAO**  \n- Joining DataBarista's network means having ownership over your data and control over how it is used.  \n- Additionally, you benefit from the value it generates for the network.  \n- More info here: [Grassroot DataDAO Simulation](https://github.com/amirmabhout/GrassrootDataDAOSimulation)  \n\n![datadao](https://imgur.com/mXZqc6Y.png)\n\n### **The Impact**  \nDataBarista transforms random networking into a **serendipitous and privacy-preserving matchmaking** experience.  \n\nIt helps people and agents form meaningful connections—without the creepy data practices. \n\n## Join DataBarista's network now: https://t.me/dataBaristaBot\n\n![intro](https://imgur.com/PSp7VwQ.png)", "logoImgData": {}, "bannerImgData": {}, "projectGithub": "databaristaAI", "projectTwitter": "databarista"}