Node categories
Text operations
Process and analyze text content
Document operations
Work with documents and files
Image operations
Analyze visual content
Data operations
Transform and enrich data
Intent Classification
Available starting with FlowX.AI 5.6.0
| Node type | Description | Use cases |
|---|---|---|
| Intent Classification | Classifies a user message into defined intents and routes to the matching branch | Chatbot routing, email triage, support ticket classification |
Configuration options
- User message — Input text to classify (supports
${}references) - Intents — Up to 10 natural language intent descriptions, each becoming an output branch
- Use memory — Include conversation history for context-aware classification
- Include rationale — Add LLM explanation for the chosen intent
- Fallback branch — Automatic “If No Intent Matches” path
Intent Classification
Learn more about configuring intents, output format, and routing behavior
Context Retrieval
Available starting with FlowX.AI 5.6.0
| Node type | Description | Use cases |
|---|---|---|
| Context Retrieval | Queries a Knowledge Base and returns matching chunks with relevance scores | RAG pipelines, document search, context gathering for downstream AI nodes |
Configuration options
- Source — Knowledge Base or Memory (Memory only available in conversational workflows)
- Knowledge Base — Select which Knowledge Base to query (when source is Knowledge Base)
- User Query — the search query, supports process variable expressions
- Search type — Hybrid (default), Semantic, or Keywords
- Max Number of Chunks — how many chunks to return (1-10)
- Min Relevance Score — minimum relevance threshold (0-100%)
- Metadata Filters — structured key-value filters (AND logic) to refine results by chunk metadata
- Use advance metadata filters — toggle for expression-based filtering
- Use Re-rank — re-rank retrieved chunks before returning
Output format
The node outputs an array of retrieved chunks, each containing:| Field | Description |
|---|---|
chunkContent | The text content of the retrieved chunk |
chunkMetadata | Metadata associated with the chunk |
relevanceScore | Similarity score between the query and the chunk |
contentSource | The content source the chunk belongs to |
Context Retrieval
Learn more about configuring Context Retrieval nodes
Custom Agent
Create custom agents with advanced capabilities powered by Model Context Protocol (MCP) tools.| Node type | Description | Use cases |
|---|---|---|
| Text generation | Create text content from prompts | Reports, summaries, responses |
| Summarization | Condense long content | Document summaries, meeting notes |
| Translation | Convert between languages | Multi-language support |
| Document completion | Fill in templates | Form letters, contracts |
Configuration options
- System prompt - Define agent behavior and constraints
Understanding nodes
Understanding nodes analyze content to extract meaning and intent.| Node type | Description | Use cases |
|---|---|---|
| Sentiment analysis | Detect emotional tone | Customer feedback, reviews |
| Topic modeling | Identify themes and subjects | Document categorization |
| Intent recognition | Understand user goals | Chatbot routing, request handling |
| Named entity recognition | Find people, places, organizations | Data extraction, compliance |
Configuration options
- Classification labels - Define categories for classification
- Confidence threshold - Minimum score for results
- Multi-label - Allow multiple classifications per input
AI Document Operations
Process documents to extract data, generate reports, or understand content.| Node | Description | Use cases |
|---|---|---|
| Document Generation | Automatically build reports or complete templates based on given inputs | Report generation, template completion |
| Document Extraction | Identify and extract structured data, entities or metadata from documents | Form processing, invoice data extraction |
| Document Understanding | Analyze documents to extract meaning, topics, sentiment, or important information | Document classification, content analysis |
| Extract Data from File | Extract text and data from documents and images with configurable extraction strategies | OCR, PDF text extraction, image data extraction, signature detection |
Extract Data from File
Learn more about configuring extraction strategies, image extraction, and signature detection
Configuration options
- Document type - Specify expected document format
- Schema definition - Define expected output structure
- Field mapping - Map extracted fields to data model
- Confidence threshold - Minimum score for extractions
AI Image Operations
Analyze visual content to generate captions, extract details, or identify objects.| Node type | Description | Use cases |
|---|---|---|
| Object recognition | Identify items in images | Document classification, damage assessment |
| Text extraction (OCR) | Read text from images | Invoice processing, ID verification |
| Scene understanding | Interpret image context | Property assessment, claims processing |
| Emotion analysis | Detect facial expressions | Customer experience, fraud detection |
Configuration options
- Detection confidence - Minimum threshold for detections
- Region of interest - Focus on specific image areas
- Output format - Structured data or annotations
Combining nodes
Nodes can be connected in workflows to create complex processing pipelines:Best practices
Start simple
Start simple
Begin with a single node and add complexity incrementally. Test each addition before moving on.
Use validation nodes
Use validation nodes
Add validation steps after extraction to ensure data quality before processing continues.
Handle errors
Handle errors
Include fallback paths for when nodes fail or return low-confidence results.
Monitor performance
Monitor performance
Track execution times and accuracy metrics to identify bottlenecks and improvement opportunities.
Related resources
Agent Builder overview
Get started with Agent Builder
Use cases
See real-world examples
Conversational workflows
Multi-turn chat with Custom Agent node changes for chat replies and memory