---
title: Knowledge Graph Exploration
description: Visual exploration of entities and relationships in your knowledge base
---


The Knowledge Graph visualization reveals connections between people, decisions, projects, and technologies in your organization. It's a powerful way to discover hidden relationships and understand organizational context.

## Opening the Graph View

Navigate to [http://localhost:8000/graph](http://localhost:8000/graph)

The graph view loads with:
- **Nodes**: Entities (people, decisions, projects, technologies)
- **Edges**: Relationships between entities
- **Initial focus**: Most connected entities

<Steps>
### Step 1: Understand node types

Different node types are color-coded:

<Tabs items={['Person', 'Decision', 'Project', 'Technology', 'Team']}>

### Person Nodes

**Color**: Blue
**Shape**: Circle

Represents:
- Team members
- Stakeholders
- External contacts

**Hover Info**:
- Name
- Role/position (if detected)
- Channels they're active in
- Message count

### Decision Nodes

**Color**: Purple
**Shape**: Diamond

Represents:
- Architectural decisions
- Product decisions
- Process changes

**Hover Info**:
- Decision title
- Date made
- Who made it
- Impact level

### Project Nodes

**Color**: Green
**Shape**: Hexagon

Represents:
- Initiatives
- Sprints
- Feature development

**Hover Info**:
- Project name
- Active dates
- Team members involved
- Status

### Technology Nodes

**Color**: Orange
**Shape**: Square

Represents:
- Tools
- Frameworks
- Libraries
- Systems

**Hover Info**:
- Technology name
- Usage context
- Related projects
- Adoption timeline

### Team Nodes

**Color**: Teal
**Shape**: Octagon

Represents:
- Departments
- Working groups
- Cross-functional teams

**Hover Info**:
- Team name
- Members
- Charter/purpose
- Related projects

</Tabs>

### Step 2: Explore relationship types

Edges show how entities relate to each other.

**Common Relationship Types:**

<Tabs items={['works_with', 'decided_by', 'uses', 'part_of', 'related_to']}>

### works_with

Connects people who collaborate frequently.

Example:
```
[@sarah] --works_with--> [@mike]
```

Hovering shows:
- How many messages they exchanged
- Common channels
- Time period of collaboration

### decided_by

Connects decisions to decision-makers.

Example:
```
[Use JWT Auth] --decided_by--> [@alex]
```

Hovering shows:
- Date of decision
- Rationale (if extracted)
- Related decisions

### uses

Connects projects or people to technologies.

Example:
```
[Payment API] --uses--> [Stripe]
[@john] --uses--> [Python]
```

Hovering shows:
- Usage context
- Frequency of mention
- Time period

### part_of

Shows hierarchical or containment relationships.

Example:
```
[Mobile App Redesign] --part_of--> [Q1 Product Launch]
```

Hovering shows:
- Scope of relationship
- Parent/child structure

### related_to

General semantic similarity.

Example:
```
[Database Migration] --related_to--> [Performance Optimization]
```

Hovering shows:
- Similarity score
- Common context

</Tabs>

### Step 3: Click to explore

Click any node to focus and expand:

**What Happens:**
1. Selected node moves to center
2. Direct neighbors (1-hop) appear
3. Related edges are highlighted
4. Sidebar shows entity details

**Entity Details Sidebar:**
- **Summary**: What this entity is
- **Related Facts**: Top facts mentioning this entity
- **Connections**: List of connected entities
- **Timeline**: When this entity appears in messages
- **Source Messages**: Link to view all messages about this entity

### Step 4: Use N-hop traversal

Explore beyond direct connections using N-hop traversal.

**How to Use:**
1. Click a node to select it
2. Use the "Expand" button (⊕) in the toolbar
3. Choose hop depth (1, 2, or 3)
4. Graph shows entities N connections away

**Use Cases:**
- **1-hop**: Direct connections (immediate collaborators)
- **2-hop**: Friends of friends (extended network)
- **3-hop**: Distant connections (organizational reach)

<Callout type="info">
**Performance Note**: 3-hop traversal on large graphs can be slow. Start with 1-hop, then expand as needed.
</Callout>

### Step 5: Filter and search

Narrow down the graph to focus on specific aspects.

**Filters (Left Panel):**
- **Node Types**: Show only certain entity types
- **Relationship Types**: Show only certain relationships
- **Date Range**: Focus on specific time period
- **Channels**: Show only from specific channels

**Search (Top Bar):**
- Search for entity names
- Auto-complete suggests matches
- Clicking a result centers the graph on that entity

**Filter Combinations:**
- "Show only Person nodes related to [@sarah]"
- "Show Decision nodes from Q1 2024"
- "Show Technology nodes used by [Project Phoenix]"

### Step 6: Export graph data

Download graph data for external analysis or visualization.

**Export Options:**
- **JSON**: Full graph with nodes, edges, metadata
- **CSV**: Node list or edge list (for spreadsheet analysis)
- **GEXF**: Import into Gephi or other network analysis tools

**To Export:**
1. Click "Export" button (top right)
2. Choose format
3. Optionally apply current filters
4. Click download

**Use Cases:**
- Organizational network analysis
- Identifying key influencers
- Understanding team structure
- Finding isolated entities (knowledge silos)

</Steps>

---

## Graph Analytics

The graph view includes built-in analytics:

**Key Metrics:**
- **Degree Centrality**: Most connected entities
- **Betweenness Centrality**: Bridge entities connecting clusters
- **PageRank**: Most influential entities
- **Communities**: Automatically detected clusters

**How to Use:**
1. Click "Analytics" tab
2. Choose metric
3. See ranked list of entities
4. Click any entity to highlight in graph

---

## Tips for Effective Graph Exploration

<Callout type="info">
**Pro Tip**: Start with a person you know and expand from there. This gives you a grounded entry point into the graph.
</Callout>

1. **Follow interesting paths**: Click through connections to discover unexpected relationships
2. **Use filters**: Large graphs are overwhelming; filter to focus
3. **Check citations**: Click entities to see source messages
4. **Look for bridges**: Entities with high betweenness connect different parts of the org
5. **Find silos**: Isolated clusters might indicate knowledge gaps

---

## Next Steps

- Learn how to [import documents](/docs/tutorials/file-import) to enrich your graph
- Set up [MCP integration](/docs/tutorials/mcp-integration) for external access
- Read the [self-hosting guide](/docs/guides/self-hosting) for production deployment
