Projects using Neo4j
Projects using Neo4j
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CHETAN MAHESHWARI
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AI Music Ops | Graph-Powered Operations Platform
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Tayyab Ali
Graph & Vector Database Architectire Development
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Marcin Wylot
RAG Solution: Document and Information Retrieval with Provenanc…
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Jonathan Popham
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GitHub - supermodeltools/docs: Save up to 40% on agent token co…
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Shabbir Abbas
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SUPERMODEL
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Ajay Bidyarthy- Full Stack AI Engineer
I’ve worked on building graph database solutions to handle complex, highly connected data that traditional relational databases struggle with. The main goal was to model relationships more intuitively and enable faster, more meaningful queries—especially for use cases like recommendations, fraud detection, and network analysis. Tech Stack ✔Graph Databases: Neo4j ✔Query Language: Cypher ✔Backend: Python (FastAPI / Flask) ✔Data Processing: Pandas ✔Visualization: Neo4j Bloom / D3.js ✔Cloud & Deployment: AWS / Docker
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Usman Haider
Retail Knowledge Graph In this project, we built a semantic knowledge graph tailored to the retail industry. The pipeline involved developing AI agents to transform heterogeneous data into standardized formats. Ontologies were created to represent domain knowledge accurately. Using Gemini models and LangChain, user queries were converted into Cypher queries to retrieve insights from a Neo4j database. We utilized an MCP server for orchestration and LangSmith for secure login and audit trails. This system enhances complex data exploration for non-technical users.
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Sergiu Nicoara
Knowledge Graph RAG: 6-Stage Retrieval on Neo4j
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Crispin Courtenay
Unified Intelligence in Venture Capital Operations
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Yash Patel
Animated Illustration of SEO Card, What do you about this? is it good or not
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Manohar Bhat
LookInsight AI : AI Customer Support Automation System Full-stack AI system that automates customer support workflows. What it does: → Classifies customer intent (complaint, inquiry, refund, support) → Detects urgency and routes to the right team → Looks up customer history via knowledge graph → Generates personalized response drafts in seconds Key features: • Real-time processing pipeline with live visualization • Multi-channel support (Email, Twitter, Slack, WhatsApp) • Business rules engine for tier-based treatment (VIP, Premium, Regular) • Neo4j knowledge graph for customer context Tech stack: Python, FastAPI, OpenAI GPT-4, Neo4j, Next.js, TypeScript Live demo: https://lookinsight.ai Skills: Python AI OpenAI FastAPI Next.js Customer Support Automation Link: https://lookinsight.ai
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Łukasz Bazan
RAMP-SENTINEL is a Tier-0 Compliance Architecture designed for the FinTech and Crypto sectors. This document is a redacted portfolio version of the Master Blueprint, showcasing an autonomous Level-2 Anti-Money Laundering (AML) investigator swarm. The primary achievement of this architecture is the elimination of the "Black-Box" liability. It replaces opaque machine learning risk scores with a transparent, deterministic graph traversal trail. By mechanically linking fiat ledgers with on-chain cryptographic data, the system drafts mathematically verified Suspicious Activity Reports (SAR) that meet the strict requirements of financial regulators (FCA, SEC, KNF). [ARCHITECTURAL IP & LIABILITY NOTICE] This document is a redacted sample of a Master Engineering Blueprint. It is intended exclusively for demonstrating architectural methodology and strategic framework design. It does not constitute a completed engineering source of truth for any third-party production environment. All proprietary frameworks and "Zero-Trust Fail-Safe" methodologies contained herein are the exclusive intellectual property of Łukasz Bazan. As a Fractional Architect, I provide the "Engineering Brain." I do not perform direct application coding. Any attempt to implement these patterns by internal teams is done at the Client’s own risk.
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Diana O
Next.js / D3js / Neo4j / OpenAI: Search Engine & Network Viz
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Syed Numan
Soocher: Consult Doctor Online
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JD Addy
Management Dashboard System for Enterprise Organisation
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Shabana Yasmin
Presidential Twitter Diplomacy & Social Network Insights
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