Knowledge Graph
Memori automatically builds a knowledge graph from your AI conversations. Each time Advanced Augmentation processes a conversation, it extracts structured relationships — semantic triples — and connects them into a graph. This powers richer recall and gives your AI deeper understanding of each user.
How It Works
- Conversation captured — Your user talks to your AI through the Memori-wrapped LLM client
- Augmentation processes — Memori Cloud analyzes the conversation in the background
- NER extraction — Named-entity recognition identifies key entities and relationships
- Triple creation — Relationships are expressed as subject-predicate-object triples
- Graph storage — Triples are stored and deduplicated in the knowledge graph
- Recall ready — The graph is available for semantic search on subsequent LLM calls
Semantic Triples
Every fact in the knowledge graph is a semantic triple — a three-part statement: [Subject] [Predicate] [Object].
- "Alice" "prefers" "dark mode"
- "PostgreSQL" "is" "a relational database"
- "The project" "uses" "FastAPI"
Example Extraction
From "My favorite database is PostgreSQL and I use it with FastAPI for our REST APIs. I've been using Python for about 8 years":
| Subject | Predicate | Object |
|---|---|---|
| user | favorite_database | PostgreSQL |
| user | uses | FastAPI |
| user | uses_for | REST APIs |
| user | uses_with | PostgreSQL + FastAPI |
| user | experience_years | Python (8 years) |
Over time, as more conversations happen, the graph grows richer. Memori connects new facts to existing ones, building a comprehensive picture of each entity.
Visualizing the Graph
The Memori Playground at app.memorilabs.ai includes a Memory Graph Viewer that shows:
| Element | What it shows |
|---|---|
| Nodes | Subjects and objects from semantic triples |
| Edges | Predicates (relationships) between nodes |
| Mention counts | How often a fact was discussed across sessions |
| Timestamps | When facts were first and last seen |
Scope
The knowledge graph follows the same scoping rules as other memory types:
| Aspect | Scope |
|---|---|
| Triples | Per entity — shared across all processes |
| Visibility | All processes for an entity can see and use the graph |
| Growth | Conversations from any process contribute to the entity's graph |
If Alice tells your support bot about PostgreSQL, your code assistant also knows she uses PostgreSQL.
Querying the Graph
The knowledge graph is automatically used during recall. When you call mem.recall() or make an LLM call through a wrapped client, Memori searches across both extracted facts and the knowledge graph to find the most relevant context.