Hybrid RAG
Most AI applications rely on standard RAG, which treats data as isolated chunks in a vector database. It finds similar words, but misses the bigger picture. Tensor Trellis combines the speed of vector search with the deep connectivity of a knowledge graph for AI that truly understands your data.
Vector Search
Fast semantic similarity search finds content that matches the meaning of your query, not just keywords. Great for discovering related documents and passages.
Knowledge Graph
Automatically maps entities, relationships, and hierarchies across your data. Your AI understands how concepts connect, not just what they say.
Three Search Methods
Vector similarity, graph traversal, and full-text search work together simultaneously. Every query benefits from all three approaches for complete, accurate answers.
Grounded Facts
Reduce hallucinations by anchoring AI responses to verified data in your knowledge graph. Every new piece of data instantly connects to what you already know.
It's the difference between an AI that searches and an AI that thinks. Traditional RAG finds words. Hybrid RAG understands context, relationships, and the structure of your entire knowledge base.