With Memgraph Lab 3.3, enters composable GraphChat
Memgraph 3.3 and Lab 3.3 are here! Alongside improvements in high availability, one of the standout features in this release is nested indices—a quite unique addition.
RAG and Why Do You Need a Graph Database in Your Stack?
Why graph databases are key to powering accurate, real-time RAG systems with LLMs and complex, connected data.
Cognee + Memgraph: How To Build An Intelligent Knowledge Graph Using Hacker News Data
Discover how to convert unstructured Hacker News content into structured, searchable insights using Memgraph’s graph database and Cognee’s AI-powered memory engine.
End-to-End Agents over Graphs with Memgraph’s AI Toolkit, LangGraph & MCP
Learn how to u Memgraph’s AI Toolkit with LangGraph and MCP to build agents that think, act, and query over graphs dynamically.
Memgraph AI Toolkit: A Codebase for Graph-Powered Applications
Discover the Memgraph AI Toolkit, an open-source Cypher-first codebase to build graph-powered AI apps using LLM agents, vector search, and GraphRAG techniques.
From Pixels to Knowledge: How We Built Visual Search Using GraphRAG
Discover how Memgraph and EBCONT turned car images into a queryable knowledge graph using a blend of computer vision, vector search, and GraphRAG in this hands-on Community Call demo.
Cypher Generation vs Tool Invocation: Designing Reliable AI for Graph Databases
Cypher generation vs tool invocation: which is better for building reliable graph-based AI assistants? Get the breakdown.
Why Knowledge Graphs Are the Ideal Structure for LLM Personalization
Find out why knowledge graphs are key to personalizing LLMs, improving context, relevance, and real-time insights with GraphRAG.
Vector Search Demo: Turning Unstructured Text into Queryable Knowledge
Discover how to turn unstructured text into a knowledge graph using Memgraph’s vector search in this hands-on demo.
Fine-Tuning LLMs vs. RAG: How to Solve LLM Limitations
Compare fine-tuning vs. RAG to overcome LLM limitations and make enterprise data accessible, dynamic, and useful.
How We Integrated 15+ Data Sources with Memgraph in a Day Using ChatGPT
Simplify loading your graph database. Learn about Memgraph's new data migration connectors for DuckDB, Spark, Iceberg, S3, and more enterprise sources.
Options for Building GraphRAG: Frameworks, Graph Databases, and Tools
Discussing the best tools, databases, and frameworks to build a powerful GraphRAG system with real-time, relevant insights.
How NASA is Using Graph Technology and LLMs to Build a People Knowledge Graph
Missed NASA’s People Graph webinar? Catch the recap and see how graph technology and AI are shaping the future of workforce intelligence.
How to build Agentic RAG with Pagerank using LlamaIndex?
Learn how to build Agentic RAG with Pagerank using LlamaIndex.
RAG isn’t dead. It’s just getting started.
Here’s what our CEO thinks about RAG and how it’s changing
How to build multi-agent RAG system with LlamaIndex?
How to build multi-agent system with Memgraph and LlamaIndex.
Introducing Updated LangChain Integration and Memgraph Toolkit for Agents
We added a support for Memgraph toolkit, to build agentic application with LangGraph and Memgraph.
Why LLMs Need Better Context?
Stop fine-tuning LLMs. Give them real-time, secure context with Memgraph to deliver accurate, personalized answers.
How to build single-agent RAG system with LlamaIndex?
How to build single-agent system with Memgraph and LlamaIndex.
Introducing the Memgraph MCP Server
We're excited to introduce the Memgraph MCP Server, a lightweight server implementation of the Model Context Protocol (MCP) designed to connect Memgraph with LLMs.
LLM Limitations: Why Can’t You Query Your Enterprise Knowledge with Just an LLM?
Why LLMs like ChatGPT can't query enterprise data and how RAG adds context to make them work for your business.
How Do LLMs Work?
How LLMs work, their limits with enterprise data, and why tools like RAG and fine-tuning help fill the gaps.
How To Do GraphRAG with DeepSeek
How FI Consulting built a scalable RAG system with Memgraph and DeepSeek—no GPU overkill, no LLM hallucinations.
GraphChat: How to Ask Questions and Talk to the Data in Your Graph DB?
Query graph data without writing Cypher. GraphChat translates plain English into queries so even non-developers can get answers.
Memgraph Lab 3.0: What’s Changed and What’s Next
Missed our webinar on Memgraph Lab 3.0? Catch up on the key updates—smarter GraphChat, real-time schema, and team collaboration!
How Would Microsoft GraphRAG Work Alongside a Graph Database?
Check out how Hierarchical GraphRAG and Memgraph 3.0 improve knowledge retrieval with Leiden community detection and structured knowledge graphs.
How To Build Agentic GraphRAG?
Ditch rigid GraphRAG pipelines—build an AI-powered agent that picks the right tool for every query. Powered by Memgraph 3.0.
Memgraph’s GraphRAG: Your Shortcut to Personalized GenAI Apps
Build smarter, faster GenAI apps with Memgraph’s GraphRAG. Use LLMs, graph databases, and dynamic algorithms for real-time insights.
Memgraph 3.0 Is Out: Solve the LLM Context Problem
A fast graph database & context engine for GenAI, powering GraphRAG, vector search, and real-time AI-driven insights.
Decoding Vector Search: The Secret Sauce Behind Smarter Data Retrieval
How to optimize semantic queries, handle high-dimensional embeddings, and query unstructured data efficiently.
Improved Knowledge Graph Creation with LangChain and LlamaIndex
Improvements to LangChain and LlamaIndex integrations simplify knowledge graph creation and enhance GraphRAG workflows.
TrustGraph and Memgraph: Knowledge Retrieval for Complex Industries
Read how TrustGraph uses chunking, GraphRAG, and Memgraph to tackle unstructured data in complex, regulated industries.
How to Extract Entities and Build a Knowledge Graph with Memgraph and SpaCy
How to extract entities from text with SpaCy, build knowledge graphs in Memgraph, and visualize insights in just a few steps!
Building a Movie Similarity Search Engine with Vector Search in Memgraph
Check out how to use Memgraph vector search to find similar movies by analyzing plot embeddings with a step-by-step guide.
Simplify Data Retrieval with Memgraph’s Vector Search
Read how Memgraph integrates vector search with graph databases for fast, semantic, and similarity-based queries.
Integrating Memgraph with LlamaIndex Building GenAI Apps
Learn how Memgraph and LlamaIndex build smarter GenAI apps by turning unstructured data into dynamic, queryable knowledge graphs.
Talking to Your Graph Database with LLMs Using GraphChat
Check out how GraphChat lets you talk to your graph database with LLMs, simplifying queries and insights.
Using Memgraph for Knowledge-Driven AutoML in Alzheimer’s Research at Cedars-Sinai
How Cedars-Sinai uses Memgraph to enhance AutoML for Alzheimer's research, driving predictive accuracy and drug discovery.
How Precina Health Uses Memgraph and GraphRAG to Revolutionize Type 2 Diabetes Care with Real-Time Insights
Precina Health using GraphRAG to help patients manage Type 2 diabetes at scale, using a mix of real-time data, AI, and personalized care.
Integrating Vector and Graph Databases: A Deep Dive into Gen AI and LLMs
Integrate vector and graph databases for AI. We cover semantic search, database optimizations, and future trends.
Building GenAI Applications with Memgraph: Easy Integration with GPT and Llama
Integrate LLMs with Memgraph using LangChain for RAG systems and build GenAI applications easily.
LLM Throws a Syntax Error Tantrum: Teaching AI to Craft Graph Style Scripts
How LLMs generate custom CSS-like GSS for dynamic graph visualization in Memgraph, training AI to create GSS.
How Microchip Uses Memgraph’s Knowledge Graphs to Optimize LLM Chatbots
Check out how Microchip uses Memgraph's graphs to enhance LLM chatbot accuracy and response quality in real-world use.
Using LLMs and Graph Database to Boost Community Engagement
Learn how LLMs and graph databases boost community engagement in our webinar with insights from Orbit's Steeve Bete.
Natural Language Querying with Memgraph Lab
Enable natural language querying in Memgraph Lab with LangChain and LLMs, bridging Cypher expertise and AI-driven queries.
