Semantic Search to Glean Valuable Insights from Podcast- Part 3

Part 2 of the tutorial walks you through extracting relationships between entities using Gemini 2.5 and building a fully connected, interactive knowledge graph in ApertureDB. It also covers visualizing the graph and highlights real-world applications in search, education, and AI pipelines.

This blog shows how to build a knowledge graph using ApertureDB and Gemini 2.5 Flash to power smarter RAG systems. Part 1 covers extracting and storing entities, enabling real-world use cases like semantic search and AI-powered customer support.

Unlock the power of GraphRAG for better AI retrieval. Learn how ApertureDB enables structured knowledge graphs for accurate, context-rich LLM responses in addition to its vector search and multimodal data management capabilities.

ApertureData and Realm Labs help developers build secure RAG chatbots by combining advanced permissions management with graph-vector storage, ensuring data protection and efficient access control.