Building a knowledge graph? Ask:
Need LLMs with more context, less hallucination?
Want to visualize risk or track assets in real-time?
Bridging structured + unstructured data?
GraphRAG solves this. Start here: github.com/FalkorDB/Gra...
#GraphRAG #KnowledgeGraph

Yesterday's 'Easily Achieve X0,000s Ops/sec with Multigraph Topology' workshop was awesome.

We started with a standalone machine with 16 cores = 26k queries per second. We tripled and then doubled the number of cores, and achieved linear scalability.
www.youtube.com/watch?v=LbeA...

Here are 4 #RAG interview questions that separate surface-level prompt hackers from true retrieval engineers. These are the questions that will become standard in hiring panels for GenAI infrastructure roles. Getting these right is what separates operators from architects.

www.falkordb.com/try-free

Large context windows (up to 1M tokens) won’t eliminate RAG:
- High latency, costs, and memory constraints.
- Performance degrades with longer texts.
- Privacy risks with unrestricted data access.

GraphRAG offers accurate, efficient retrieval. How are you managing these trade-offs?

#rag #llm

Pure semantic search struggles with relational queries. Hybrid retrieval—vector embeddings plus graph queries—is the fix. FalkorDB + LangChain + LangGraph handles this efficiently. How's your RAG stack handling this?

Generative AI demands real-time reasoning, but traditional databases struggle with dynamic data. At NVIDIA's AI conference, FalkorDB will show how knowledge graphs power LLM workflows (e.g., GraphRAG) & fraud detection.
Think graph-native storage is the future?

LLMs + memory = game-changer. FalkorDB's graph DB now integrates with LangChain, enabling AI agents to retain context across interactions. Dive into the tech: optimized queries, scalable architecture, and simplified dev workflow. Curious?

Check out the guide: www.falkordb.com/blog/buildin...

NoLiMA: GPT-4o's accuracy drops from 99.3% to 69.7% when context expands from <1K to 32K tokens. Scaling context windows alone can't overcome the inability to model latent relationships. Property graphs = missing layer (explicit relationship encoding, metadata-aware retrieval).

New website, new look, still the fastest.
www.falkordb.com

#GenAI #LLM #GraphRAG #RAG

How much of your enterprise data do you send to an LLM?

#RAG #LLM #EnterpriseData #KnowledgeGraph #GraphRAG

Apple’s AI errors highlight why grounding outputs in verifiable data is critical. Sensitive domains like news or healthcare can’t afford misinformation. Graph-based RAG systems offer a way forward. Is your AI ready for this challenge?
#rag #graph #genai

Join FalkorDB's CTO for a deep dive into writing efficient Cypher queries. Learn how to optimize query paths, handle complex traversals, and avoid bottlenecks when scaling graph workloads.

🗓️ 18 Feb 2025 | ⏰ 9:30 AM PST / 19:30 PM IST
🔗 Sign up: lu.ma/b2npiu4r