Agentic RAG
Agentic RAG enhances retrieval accuracy through LLM-powered agents that process queries intelligently before retrieval.What is Agentic RAG?
Agentic RAG extends traditional RAG by adding an intelligent, agent-driven control layer that can reason about tasks, determine required information, and actively shape the context used during generation. Instead of a static pipeline, Agentic RAG operates as a coordinated reasoning system that can plan, adapt, validate, and refine steps in real time.RAG Agents
| Agent | Purpose | Example |
|---|---|---|
| Query Type Detection | Determines if user seeks a specific answer or search results list | Classifies query intent with confidence level |
| Query Transformation | Identifies key terms, removes noise, prioritizes relevant documents | Query: “What is the work-from-home policy for Kore.ai?” → Extracts: “work-from-home”, “policy”, “Kore.ai” |
| Metadata Extractor | Extracts sources and fields from query, maps to structured data, applies filters | Query: “Find Jira tickets assigned to John with status ‘In Progress’” → Applies: assignee=John, status=In Progress |
Supported Models
Currently, only OpenAI and Azure OpenAI 4.0 models are supported for Agentic RAG.Enabling Agentic RAG
- Navigate to Configuration > Agentic RAG
- Enable Agentic RAG (enables all agents by default)
- All agents use the configured model
Customizing Agents
To change model/prompt settings or enable/disable specific agents:- Go to Generative AI Tools > GenAI Features
- Configure individual agent settings
Considerations
| Factor | Impact |
|---|---|
| Response Time | Multiple LLM calls may increase overall response time |
| API Usage | Enable agents only when utilizing search results via API |
| Accuracy | Improves retrieval precision for complex queries |
Business Rules
Business Rules customize and personalize answers based on organizational requirements and policies.Purpose
Business rules define how results are promoted, positioned, or filtered. Use cases include:- Personalized recommendations
- Promotional offers
- Content filtering
- Access control
- Language-based prioritization
How Business Rules Work
- User query received
- Relevant chunks retrieved from Answer Index
- Business rules evaluate conditions
- Chunks filtered/modified based on rule outcomes
- Filtered chunks used for answer generation
Rule Types
Contextual Rules - Use context information (user profile, geography, search history) to specify conditions and actions.Defining Business Rules
Each rule consists of:| Component | Description |
|---|---|
| Name | Unique identifier for the rule |
| Conditions | Criteria that trigger the rule (based on context variables) |
| Outcomes | Actions performed when conditions are met |
Condition Configuration
Select Context - Specify the context variable for the condition. Dynamic suggestions show available variables. Custom Data - UsecustomData field from Search APIs for business rules. Example: customData.userContext.location
Outcome Actions
| Action | Description | Factor Range |
|---|---|---|
| Boost | Prioritize chunks by boost factor | 1-5 (5 = maximum boost) |
| Lower | De-prioritize results by lower factor | 1-5 |
| Hide | Remove from search results | - |
| Filter | Filter results as per response criteria | - |
Response Configuration
Define which chunks the action applies to using chunk fields and values. Example: To target chunks where title contains ‘Confidential’:- Field:
chunkTitle - Operator:
contains - Value:
Confidential
Example Business Rule
Scenario: Restrict confidential information to managers in a specific department.| Component | Configuration |
|---|---|
| Condition | userContext.dept does not equal [target_dept] |
| Action | Hide |
| Response | Chunks where chunkTitle contains Confidential |
Important Notes
- Multiple conditions use logical AND (all must be satisfied)
- Multiple outcomes use logical AND (all are applied)
- Values are case-sensitive and use entire word matching
- Example: “Confidential” ≠ “confidential” ≠ “confidentially”
Managing Business Rules
| Action | Steps |
|---|---|
| Add Rule | Click +Contextual Rule button |
| Activate/Deactivate | Use slider button in rules list |
| Edit Rule | Select rule from list, make changes, click Save |
| Delete Rule | Open rule details, click Delete button |
Quick Reference
Agentic RAG Agents
| Agent | Function |
|---|---|
| Query Type Detection | Answer vs. Search Results classification |
| Query Transformation | Key term extraction, noise removal |
| Metadata Extractor | Filter and boost application |
Business Rule Actions
| Action | Effect |
|---|---|
| Boost (1-5) | Increase chunk priority |
| Lower (1-5) | Decrease chunk priority |
| Hide | Remove from results |
| Filter | Apply field-based filtering |