Airgentic Help
The Conversational Intelligence screen is where you configure the automated topic clustering and category classification that powers the Categories & Themes insights.
This guide covers how to create taxonomies (your own category structures) and configure the topic/theme clustering that automatically discovers what customers are asking about.
Navigate to Conversational Intelligence from the main admin menu. This screen has two main tabs:
A taxonomy is a classification system you define to organise customer questions according to your business structure. Unlike themes (which are discovered automatically), taxonomies give you governed, consistent categories that align with your organisation.
| Setting | Description |
|---|---|
| Name | A human-readable name shown in reports (e.g., "Schools and Departments") |
| Category Type | What kind of categories this contains — helps organise your taxonomies |
| Assignment Mode | Single assigns each question to exactly one category (use for routing). Multiple allows questions to have several categories (use for tagging) |
| Hierarchical categories | Enable if categories have parent-child relationships (e.g., Department > Team) |
| Apply to all services | When checked, the taxonomy applies to all services in your account |
Choose the type that best describes your categories:
After creating a taxonomy, switch to the Categories tab to add your classification labels.
| Field | Description |
|---|---|
| Label | The display name (e.g., "Undergraduate Admissions") |
| Parent Category | Optional — nest under another category to create hierarchy |
| Description | What questions belong here — helps with training |
| Owner | The person or team responsible for this category |
| Owner Email(s) | Email addresses for notifications (comma-separated) |
| Status | Active categories are used; Inactive are hidden but preserved |
| Sort Order | Controls display order (lower numbers appear first) |
Each category can have training sources that help the AI understand what belongs there. Click on a category row to see and manage its training sources.
Training source types:
| Type | Description |
|---|---|
| Fetch pages with URL prefix | Retrieves pages from your indexed content matching a URL pattern. The system extracts relevant text to build training data. |
| Text Brief | Freeform description of what the category covers. Useful when URL-based training isn't available. |
| Exemplar Question | A sample question that should match this category. Add several variations for best results. |
| Negative Exemplar | A question that should NOT match this category. Helps distinguish similar categories. |
The more training data you provide, the more accurate the classification becomes.
Taxonomies start in Draft status, allowing you to refine them before use.
When ready:
The system will:
1. Build training data from your sources (progress shown in the header)
2. Generate semantic embeddings for each category
3. Make the taxonomy available for classification
Once published, certain settings become locked to maintain classification stability. You can still edit category names, owners, and emails.
If you need to change locked settings on a published taxonomy:
The new version will replace the previous one for future classifications.
Once published, click Classify Conversations to:
Classification also runs automatically after each nightly clustering analysis.
The Reports tab shows how well your taxonomy is performing:
Shows how many questions have been assigned to each category, broken down by:
Track each category over time:
Click Review to see individual questions and provide feedback.
The Near Matches tab shows questions where two or more categories scored nearly identically (within 4%). These are worth reviewing to:
The Unassigned tab shows questions that didn't meet the confidence threshold for any category. These may represent:
Use this to identify missing categories or add training examples.
The Topics and Themes section configures the automated clustering that discovers what customers are asking about.
Use the Enable Topic & Theme Clustering toggle to turn clustering on or off for this service.
Disabling clustering does not delete existing themes — it simply stops new analysis runs. You can re-enable it at any time.
Each month, the system:
This happens automatically on a nightly schedule, but you can also trigger manual analyses.
The status panel shows:
Click New Analysis to trigger clustering for the selected month. This is useful when:
The dropdown lets you select which month to view or analyse. Each month has its own clustering run, allowing you to track how themes evolve over time.
If you need to start fresh, click Reset Themes to:
After resetting, run a new analysis to create fresh themes based on your current data.
Warning: This action cannot be undone.
For most use cases, the default settings work well. However, advanced users can adjust clustering behaviour:
| Setting | Description | Default |
|---|---|---|
| Min Cluster Size | Smallest number of similar questions to form a cluster | 5 |
| Min Samples | How many similar neighbours a question needs | 3 |
| Cluster Merge Distance | Distance threshold for merging similar clusters (0 = no merging) | 0 |
| Cluster Selection | EOM finds stable clusters; Leaf keeps smallest clusters | EOM |
| Distance Metric | How similarity is measured (Euclidean or Cosine) | Euclidean |
| Dimensionality Reduction (UMAP) | Reduces embedding dimensions before clustering | Enabled |
Warning: Changing these from defaults will likely impact clustering quality unless you have a specific reason.
Both taxonomies and themes update automatically:
| Time (UTC) | Process |
|---|---|
| 03:30 | Clustering — Groups questions into clusters and maps to themes |
| 04:00 | Classification — Assigns questions to published taxonomy categories |
This means insights are typically updated by early morning each day.