Tensor Trellis
Standard RAG misses context. Tensor Trellis combines vector search with knowledge graphs to build AI systems that actually understand your data — with infinite memory and agent hierarchies that scale.
Standard RAG
Vector search alone
- ❌ Loses context between chunks
- ❌ Can't reason about relationships
- ❌ Hallucinates when context is ambiguous
- ❌ No structural understanding of data
- ❌ Memory limited to context window
Hybrid RAG
Vector + Knowledge Graph
- Full context preservation across documents
- Relationship-aware retrieval
- Graph-grounded answers reduce hallucination
- Structural + semantic understanding combined
- Infinite memory via persistent knowledge graphs
Core Capabilities
Hybrid RAG Engine
Combines dense vector retrieval (semantic) with sparse graph traversal (structural) for retrieval accuracy that either method alone can't achieve.
Agent Hierarchy
Deploy teams of AI agents with defined roles, authority levels, and escalation paths. Lead agents coordinate, specialists execute, humans approve.
Infinite Memory
Agents retain context across sessions using persistent knowledge graphs and cognitive memory. No more starting from scratch every conversation.
Persona System
Create specialized AI personas with domain expertise, behavioral rules, and knowledge scopes. Each persona maintains its own memory and personality.
Integrations
Connect to existing tools and data sources. API-first architecture makes Tensor Trellis a knowledge layer for your entire stack.
Self-Hosted
Run on your own infrastructure. Your knowledge graph, your embeddings, your data — never leaves your control. No cloud dependency.
How It Works
From raw data to intelligent retrieval in four steps
Ingest
Feed documents, databases, or APIs into the system. Automatic chunking, embedding, and entity extraction.
Graph
Build a knowledge graph from extracted entities and relationships. Connect concepts across documents.
Retrieve
Hybrid retrieval combines vector similarity with graph traversal for context-rich, accurate results.
Act
AI agents use retrieved knowledge to answer questions, complete tasks, or escalate to humans.