Power AI Agents with Graph-Native Knowledge
Build GraphRAG systems, ground LLMs with structured knowledge, and enable intelligent agents with TuringDB's ultra-fast graph database optimized for AI workloads.
LLM & Agentic AI Use Cases
GraphRAG
Enhance LLM responses with structured knowledge graphs for more accurate and contextual outputs.
- Knowledge graph grounding
- Contextual retrieval
- Hallucination reduction
Agents
Build agents that can navigate complex knowledge graphs to make informed decisions.
- Multi-hop reasoning
- Dynamic planning
- Tool orchestration
Knowledge Management
Organize and query enterprise knowledge for AI-powered search and question-answering systems.
- Semantic search
- Entity linking
- Relationship discovery
Why Use TuringDB for AI?
Sub-Millisecond Retrieval
Retrieve relevant context from knowledge graphs in under 1ms. Enable real-time AI applications without latency bottlenecks in your RAG pipeline.
Multi-Hop Reasoning
Navigate complex relationships across millions of entities. Support sophisticated AI reasoning with deep graph traversals at scale.
Dynamic Knowledge Updates
Update knowledge graphs in real time without blocking AI queries. Zero-lock concurrency ensures your AI agents always have access to the latest information.
Rich Metadata Support
Store embeddings, timestamps, confidence scores, and custom metadata alongside graph relationships. Perfect for AI systems with hybridised symbolic and neural approaches.
Build Smarter AI with TuringDB
Use TuringDB to power GraphRAG systems, hybrid search and LLM agents.