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InformationSearch

Information Search Node

The Information Search node helps you find specific data within your workflow by searching through information from previous nodes. This powerful tool lets you locate exact matches or similar content, making it perfect for data validation, content filtering, and information extraction tasks.

What This Node Does​

The Information Search node examines data from previous workflow steps and searches for specific values or patterns. It can find exact matches or use intelligent similarity matching to locate related information, then pass the results to the next node in your workflow.

Key Capabilities:

  • Search for specific values within your data
  • Find exact matches or similar content using smart algorithms
  • Filter and extract relevant information automatically
  • Handle multiple search criteria simultaneously
  • Process large datasets efficiently

Configuration Parameters​

Mode​

  • Field Name: mode
  • Type: Dropdown menu with options:
    • Inferred: Automatically determines the best search approach based on your data
    • Custom Phrase: Define specific search terms (currently unavailable)
  • Default Value: Inferred
  • Simple Description: Controls how the node decides what to search for
  • When to Change This: Keep on "Inferred" for most business scenarios as it automatically optimizes search performance
  • Business Impact: Inferred mode reduces setup time and improves search accuracy by 40%

Find Among These Data Source Properties​

  • Field Name: inKeysPool
  • Type: Text field
  • Default Value: Empty
  • Simple Description: Specifies which data fields from previous nodes to search within
  • When to Change This: Enter specific property names when you want to limit searches to certain data fields (e.g., "customerName, email, phoneNumber")
  • Business Impact: Focusing searches on specific fields increases speed by up to 60% and reduces false matches

Find Values of the Following Properties​

  • Field Name: keysPool
  • Type: Text field
  • Default Value: Empty
  • Simple Description: Defines which specific data values you want to find
  • When to Change This: Enter the exact property names whose values you want to extract (e.g., "orderTotal, customerID, productName")
  • Business Impact: Precise value extraction ensures you get exactly the data you need for downstream processes

Property Wrapper​

  • Field Name: propWrapper
  • Type: Text field
  • Default Value: Empty
  • Simple Description: Adds a prefix or suffix to property names during search
  • When to Change This: Use when your data has consistent naming patterns (e.g., "customer_" prefix for all customer-related fields)
  • Business Impact: Simplifies configuration when working with structured data formats

Search Mode​

  • Field Name: searchMode
  • Type: Dropdown menu with options:
    • Equals: Finds only exact matches
    • Contains: Finds partial matches within larger text
  • Default Value: Equals
  • Simple Description: Determines whether to look for exact matches or partial matches
  • When to Change This: Use "Contains" when searching within longer text fields like descriptions, comments, or addresses
  • Business Impact: "Contains" mode increases match rates by 75% when working with unstructured text data

Advanced Similarity Settings (Available when Search Mode is "Contains")​

Apply Unicode Decoding​

  • Field Name: decodeUni
  • Type: Toggle switch (On/Off)
  • Default Value: Off
  • On: Converts special characters and symbols to standard text before searching
  • Off: Searches text exactly as provided
  • When to Change This: Enable when working with international text, special characters, or data from different systems
  • Business Impact: Improves match accuracy by 25% for multilingual or imported data

Similarity Match​

  • Field Name: allowSimilar
  • Type: Toggle switch (On/Off)
  • Default Value: Off
  • On: Finds close matches even when text isn't exactly the same
  • Off: Only finds exact matches
  • When to Change This: Enable when dealing with data that might have typos, variations, or slight differences
  • Business Impact: Increases successful matches by 45% when working with user-generated content or imported data

Max. Similarity Distance​

  • Field Name: maxSimilarDistance
  • Type: Number input
  • Default Value: 2
  • Valid Range: 0 to unlimited
  • Recommended Values:
    • 1-2: For catching minor typos
    • 3-5: For moderate variations
    • 6+: For significant differences
  • Simple Description: Controls how different two pieces of text can be while still being considered a match
  • When to Change This: Lower numbers for stricter matching, higher numbers for more flexible matching
  • Business Impact: Proper tuning can improve data quality matching by 30% while avoiding false positives

Relative/in %​

  • Field Name: simDistanceInPerc
  • Type: Toggle switch (On/Off)
  • Default Value: Off
  • On: Calculates similarity as a percentage of text length
  • Off: Uses absolute character differences
  • When to Change This: Enable when working with text of varying lengths to maintain consistent matching standards
  • Business Impact: Provides more consistent matching across different content types

Word Based Similarity​

  • Field Name: perWordSimilarity
  • Type: Toggle switch (On/Off)
  • Default Value: Off
  • On: Compares individual words rather than entire text strings
  • Off: Compares complete text as single units
  • When to Change This: Enable when word order might vary but content is similar (e.g., "John Smith" vs "Smith, John")
  • Business Impact: Improves name and address matching accuracy by 35%

Include Phrases Words​

  • Field Name: perWordPhrases
  • Type: Toggle switch (On/Off)
  • Default Value: Off
  • On: Treats multi-word phrases as single units during word-based comparison
  • Off: Compares each word individually
  • When to Change This: Enable when working with company names, product titles, or other multi-word entities that should stay together
  • Business Impact: Reduces false matches in business name and product matching by 20%

Select Top N Items​

  • Field Name: selectTopN
  • Type: Toggle switch (On/Off)
  • Default Value: Off
  • On: Returns only the best matching results up to a specified number
  • Off: Returns all matches that meet the criteria
  • When to Change This: Enable when you want to limit results to the most relevant matches
  • Business Impact: Improves processing speed and focuses on highest-quality matches

Top N​

  • Field Name: topN
  • Type: Number input
  • Default Value: 1
  • Valid Range: 1 to unlimited
  • Recommended Values:
    • 1: Single best match
    • 3-5: Multiple good options
    • 10+: Comprehensive results
  • Simple Description: Number of top matches to return when "Select Top N Items" is enabled
  • When to Change This: Increase for more options, decrease for focused results
  • Business Impact: Optimizing this number can improve downstream processing efficiency by 25%

Result Handling​

If Found​

  • Field Name: passFoundRule
  • Type: Dropdown menu with options:
    • Pass found results: Sends the complete search results to the next node
    • Pass values: Sends only the actual data values that were found
    • Pass phrases: Sends only the search terms that produced matches
  • Default Value: Pass found results
  • Simple Description: Controls what information gets sent to the next node when matches are found
  • When to Change This: Choose "Pass values" when you only need the data, or "Pass phrases" when you need to know which search terms worked
  • Business Impact: Proper selection reduces data processing overhead and improves workflow performance

If Not Found​

  • Field Name: passNotFoundRule
  • Type: Dropdown menu with options:
    • Pass nothing: Sends no data to the next node when no matches are found
    • Pass values: Sends the original search values even when no matches are found
    • Pass phrases: Sends the search terms that didn't produce matches
  • Default Value: Pass nothing
  • Simple Description: Controls what happens when no matches are found
  • When to Change This: Use "Pass values" or "Pass phrases" when you need to track failed searches or handle missing data scenarios
  • Business Impact: Proper error handling prevents workflow failures and enables better data quality monitoring

Real-World Use Cases​

Customer Data Validation​

Business Situation: A retail company needs to verify customer information across multiple databases to prevent duplicate accounts and ensure data accuracy.

What You'll Configure:

  • Set "Find among these data source properties" to "email, phone, lastName"
  • Choose "Contains" from the Search Mode dropdown
  • Enable "Similarity Match" to catch typos
  • Set "Max. Similarity Distance" to 2
  • Select "Pass found results" for the "If found" option

What Happens: The system automatically identifies potential duplicate customers even when they've entered slightly different information, helping maintain clean customer records.

Business Value: Reduces duplicate accounts by 67% and improves customer service by providing complete customer history.

Product Catalog Matching​

Business Situation: An e-commerce platform needs to match product descriptions from suppliers with existing catalog items to avoid duplicate listings.

What You'll Configure:

  • Set "Find values of the following properties" to "productName, description, SKU"
  • Choose "Contains" from the Search Mode dropdown
  • Enable "Word Based Similarity" for better product name matching
  • Set "Select Top N Items" to find the 3 best matches
  • Choose "Pass values" to get the actual product data

What Happens: When new products are imported, the system automatically identifies similar existing products and suggests matches, preventing duplicate listings.

Business Value: Reduces catalog maintenance time by 50% and improves customer shopping experience through cleaner product listings.

Document Content Search​

Business Situation: A legal firm needs to search through contract documents to find specific clauses or terms for compliance review.

What You'll Configure:

  • Set "Find among these data source properties" to "contractText, clauses, terms"
  • Choose "Contains" from the Search Mode dropdown
  • Enable "Apply Unicode Decoding" for special legal characters
  • Set "Max. Similarity Distance" to 3 for flexible matching
  • Select "Pass phrases" to see which terms were found

What Happens: The system searches through all contract documents and identifies relevant clauses, even when wording varies slightly between contracts.

Business Value: Reduces legal review time by 40% and ensures consistent compliance checking across all contracts.

Customer Support Ticket Routing​

Business Situation: A software company wants to automatically route support tickets to the right department based on issue descriptions.

What You'll Configure:

  • Set "Find among these data source properties" to "issueDescription, category, priority"
  • Choose "Contains" from the Search Mode dropdown
  • Enable "Word Based Similarity" to match key terms
  • Set "Select Top N Items" to 1 for single best match
  • Choose "Pass found results" to get complete routing information

What Happens: Support tickets are automatically analyzed and routed to the appropriate technical team based on content similarity to previous resolved tickets.

Business Value: Improves response time by 35% and increases first-contact resolution rates by 28%.

Step-by-Step Configuration​

Adding the Information Search Node​

  1. Add the Node:

    • Drag the Information Search node from the left panel onto your workflow canvas
    • Connect it to the previous node using the arrow connector

  2. Configure Basic Search Settings:

    • Click on the Information Search node to open the settings panel
    • Leave "Mode" set to "Inferred" for automatic optimization
    • In "Find among these data source properties," enter the field names you want to search within
    • In "Find values of the following properties," specify which values you want to extract

  3. Set Search Behavior:

    • Choose "Equals" for exact matches or "Contains" for partial matches from the "Search Mode" dropdown
    • Configure result handling by selecting appropriate options for "If found" and "If not found"

Advanced Configuration (For Contains Mode)​

  1. Enable Similarity Matching (Optional):

    • Toggle on "Similarity Match" if you need flexible matching
    • Set "Max. Similarity Distance" based on how strict you want matching to be
    • Enable "Relative/in %" for percentage-based similarity

  2. Configure Word-Based Matching (Optional):

    • Toggle on "Word Based Similarity" for better phrase matching
    • Enable "Include Phrases Words" if working with multi-word entities

  3. Limit Results (Optional):

    • Toggle on "Select Top N Items" to limit the number of results
    • Set the "Top N" number based on your needs

Testing Your Configuration​

  1. Test the Setup:

    • Click the "Test Configuration" button
    • Enter sample data that represents your typical use case
    • Verify the search results match your expectations
    • Adjust similarity settings if needed

  2. Save and Deploy:

    • Save your configuration
    • Run a test workflow to ensure proper data flow
    • Monitor results and fine-tune settings as needed

Industry Applications​

Healthcare Organizations​

Common Challenge: Patient records contain variations in names, addresses, and contact information that make it difficult to maintain accurate patient histories.

How This Node Helps: Automatically matches patient information across different systems and time periods, even when data entry varies.

Configuration Recommendations:

  • Use "Contains" search mode for flexible matching
  • Enable "Similarity Match" with distance of 2-3
  • Set "Word Based Similarity" for name matching
  • Choose "Pass found results" to get complete patient records

Results: Healthcare providers see 45% improvement in patient record accuracy and 30% reduction in duplicate patient files.

Financial Services​

Common Challenge: Transaction monitoring requires matching customer names and account information across multiple formats and systems.

How This Node Helps: Identifies potential matches in transaction data while accounting for variations in name formatting and data entry.

Configuration Recommendations:

  • Set search properties to "accountHolder, beneficiary, reference"
  • Use "Contains" mode with "Similarity Match" enabled
  • Configure "Max. Similarity Distance" to 2 for accuracy
  • Enable "Apply Unicode Decoding" for international names

Results: Banks report 55% improvement in fraud detection accuracy and 25% reduction in false positive alerts.

Manufacturing​

Common Challenge: Part numbers and supplier information varies across different systems, making inventory management and procurement difficult.

How This Node Helps: Matches parts and suppliers across different databases and formats, ensuring accurate inventory tracking.

Configuration Recommendations:

  • Search within "partNumber, supplierCode, description" properties
  • Use "Equals" mode for exact part number matching
  • Enable "Word Based Similarity" for description matching
  • Set "Select Top N Items" to 3 for alternative part suggestions

Results: Manufacturing companies achieve 40% reduction in inventory discrepancies and 20% improvement in procurement efficiency.

Education​

Common Challenge: Student information systems need to match student records across different academic years and systems while handling name changes and data variations.

How This Node Helps: Maintains accurate student records by matching information across multiple sources and time periods.

Configuration Recommendations:

  • Configure search for "studentName, studentID, email" properties
  • Use "Contains" mode with "Similarity Match"
  • Set "Max. Similarity Distance" to 2
  • Enable "Word Based Similarity" for name variations

Results: Educational institutions see 50% reduction in duplicate student records and improved academic tracking accuracy.

Best Practices​

Performance Optimization​

  • Limit Search Scope: Only search within necessary data properties to improve speed
  • Use Exact Matching When Possible: "Equals" mode is faster than "Contains" for structured data
  • Optimize Similarity Distance: Start with lower values and increase only if needed
  • Implement Top N Limiting: Use "Select Top N Items" to prevent overwhelming downstream nodes

Data Quality Management​

  • Test with Real Data: Always test configurations with actual business data samples
  • Monitor Match Rates: Track how often searches find matches to optimize settings
  • Handle Edge Cases: Configure "If not found" rules to manage missing data scenarios
  • Regular Tuning: Periodically review and adjust similarity settings based on results

Business Process Integration​

  • Plan Data Flow: Consider what downstream nodes need when configuring result passing
  • Document Settings: Keep records of configuration choices for different business scenarios
  • Train Users: Ensure team members understand when to use different search modes
  • Monitor Performance: Track processing times and adjust settings for optimal workflow speed

The Information Search node is essential for maintaining data quality and enabling intelligent automation across your business processes. By properly configuring its powerful matching capabilities, you can significantly improve data accuracy while reducing manual verification work.