Neo4j launched Virtual Graph, a zero-copy, zero-ETL solution that brings native graph intelligence to Databricks and Snowflake, enabling Cypher queries and graph algorithms directly on existing cloud …
A developer built StudyMate AI, a voice-first tutoring system for ICSE/CBSE students that tracks cognitive state over time using a behavioral graph in Neo4j. Unlike typical AI tutors, it classifies st…
A developer built myRAG, a fully self-hosted RAG stack combining FastAPI, React, Qdrant, PostgreSQL, and Neo4j. The system uses hybrid search with dense and sparse embeddings, cross-encoder reranking,…
A developer compares Mem0 and TurboMem as memory layers for TypeScript AI agents. TurboMem runs as a native TypeScript library inside the process, avoiding the separate service and infrastructure requ…
Neo4j relaunched its GraphAcademy learning platform with an AI assistant called E.L.A.I.N.E. and a new MCP server for IDE integration. The platform offers free hands-on courses and labs for learning C…
Neo4j partnered with RocketRide, Butterbase, Daytona, Nebius, and Opsera at HackwithBay 3.0, where 200 builders used graph databases to build thoughtful agents for productivity. First-place team VeriG…
Four open-source projects—Graphiti, Hindsight, Mem0, and others—offer expanded memory capabilities for AI agents and large language models, using techniques like temporal knowledge graphs and multi-st…
Neo4j's Aura Agent Hackathon drew 40 AI agent submissions from developers worldwide, with winners including a misinformation-mapping ConspiracyGraph Agent and a regulatory-risk graph agent, demonstrat…
Neo4j launched a redesigned GraphAcademy with a hands-on Neo4j Fundamentals course, editable data models, team learning features, an onboarding assistant, and public learner profiles. The update aims …
Neo4j argues that most enterprise AI projects fail due to data that lacks context, flexibility, and standardization, and introduces a knowledge layer to make data AI-ready. Gartner reports 63% of orga…
FlowMind, an AI-powered group project manager built at HackHazards '26, uses persistent memory to learn team patterns and predict failures before they happen. The system combines Groq's LLM, Hindsight…
A developer shares seven key lessons learned from building modern AI agents with Neo4j, GraphRAG, Aura Agents, and LLM Mesh. The lessons cover graph databases, persistent memory, GraphRAG vs. traditio…
Researchers have developed a CVE-TTP Knowledge Graph linking software vulnerabilities to attacker behaviors using the MITRE ATT&CK framework. Transformer-based models like CySecBERT achieved high F1-s…
Neo4j's MCP server can now be run locally with Docker, bypassing the need for GitHub Codespaces and their free-tier limits. A docker-compose setup launches both Neo4j and the MCP server, enabling deve…
A company running a self-hosted AI business platform since early 2026 shares seven painful lessons from building production RAG systems, including the need for document-type-aware chunking and hybrid …
SynapCores released official LlamaIndex integration packages for its AI-native SQL engine, enabling RAG, GraphRAG, and hybrid retrieval in a single self-hosted binary. The packages replace multiple da…
Researchers developed a provenance-aware, knowledge-graph-based multi-agent framework that integrates 466,525 Reddit posts, 60,782 WebMD reviews, and 20 years of FDA adverse event data for nine antide…
Neo4j Chief Scientist proposes that AI agents require three types of structured memory—long-term, short-term, and reasoning memory—organized as context graphs to ensure reliability and accuracy in aut…
Graphify, a new tool, converts codebases and notes into queryable knowledge graphs to provide AI agents with persistent, efficient memory, reducing token costs and improving precision over vector sear…
Neo4j has been named a 'One to Watch' in Snowflake's 2026 Modern Marketing Data Stack Report for its graph database and analytics integration with Snowflake's AI Data Cloud, enabling advanced graph-dr…