FlowX.AI Data Search

The Data Search service enables you to find specific data across process instances within your FlowX.AI platform. It uses Elasticsearch to perform fast, indexed searches across process data.

Simple Search

Search by a single field and value

Advanced Search

Search using multiple criteria simultaneously

Cross-Application

Search across multiple applications

Date Filtering

Filter results by process creation dates

Prerequisites

Before using the Data Search service, ensure you have:

Elasticsearch Configuration

Kafka Topics

Process Data

Quick start

Set up your data process

Create a process that stores searchable data and configure field indexing.

Create a search process

Build a process with Kafka Send/Receive actions for search functionality.

Configure search parameters

Define your search criteria using simple or advanced syntax.

Handle search results

Process the returned data and display results to users.

1. Set up your data process

First, create a process that contains searchable data. Add a Service Task with a business rule:

output.put("application", {
  "client": {
    "personalInfo": {
      "firstName": "Sarah",
      "lastName": "Johnson", 
      "email": "sarah.johnson@techcorp.com",
      "phone": "+1-555-0101"
    },
    "address": {
      "country": "USA",
      "city": "San Francisco", 
      "state": "California",
      "zipCode": "94102"
    },
    "business": {
      "company": "TechCorp Inc",
      "industry": "Technology",
      "position": "CTO"
    },
    "account": {
      "type": "Premium",
      "status": "Active",
      "riskLevel": "Low"
    }
  }
});

Critical Step: After creating your data structure, you must configure field indexing in Process Settings → Data Search for the search to work.

Configure Field Indexing

Navigate to Process Settings → Data Search and add the field paths you want to search:

Fields that we indexed in our example:

application.client.personalInfo.firstName
application.client.personalInfo.lastName
application.client.personalInfo.email

2. Create your search process

Create a new process with a Send Message Task:

Configuration:

Action Type: Kafka Send Action
Topic: KAFKA_TOPIC_DATA_SEARCH_IN

3. Configure search parameters

Choose your search approach based on your needs:

Use when searching by a single field:

{
  "searchKey": "application.client.personalInfo.lastName",
  "value": "Johnson",
  "processDefinitionNames": ["client_process"],
  "states": ["FINISHED"]
}

Use when searching by a single field:

{
  "searchKey": "application.client.personalInfo.lastName",
  "value": "Johnson",
  "processDefinitionNames": ["client_process"],
  "states": ["FINISHED"]
}

Use when searching by multiple criteria (AND logic):

{
  "searchKeys": [
    {"key": "application.client.personalInfo.firstName", "value": "Sarah"},
    {"key": "application.client.personalInfo.lastName", "value": "Johnson"}
  ],
  "processDefinitionNames": ["client_process"],
  "states": ["FINISHED"]
}

All conditions in searchKeys must match for a result to be returned.

Search across multiple applications:

{
  "searchKey": "application.client.account.type",
  "value": "Premium",
  "applicationIds": [
    "app-1-uuid",
    "app-2-uuid"
  ]
}

Filter by process creation dates:

{
  "searchKey": "application.client.business.industry",
  "value": "Technology",
  "processStartDateAfter": "2024-01-01T00:00:00Z",
  "processStartDateBefore": "2024-12-31T23:59:59Z",
  "states": ["FINISHED"]
}

4. Handle search results

Add a Receive Message Task with:

Data Stream: KAFKA_TOPIC_DATA_SEARCH_OUT

Success response example:

{
  "result": [
    {
      "processInstanceUUID": "b743ac99-4029-4b93-9ac3-4a45b4a62673",
      "state": "FINISHED",
      "processStartDate": "2025-05-28T12:18:50.532Z",
      "data": {
        "application": {
          "client": {
            "personalInfo": {
              "firstName": "Sarah",
              "lastName": "Johnson"
            }
          }
        }
      }
    }
  ],
  "tooManyResults": false,
  "success": true
}

Search parameters reference

Quick reference table

Parameter	Type	Mandatory	Description	Example
`searchKey`	String	Yes	Single field path to search	`"application.client.personalInfo.lastName"`
`value`	String	Yes	Value to search for (with searchKey)	`"Johnson"`
`searchKeys`	Array	Yes (if multiple fields)	Multiple field-value pairs (AND logic)	`[{"key": "field1", "value": "val1"}]`
`processDefinitionNames`	Array	Yes	Limit to specific processes	`["client_onboarding"]`
`applicationIds`	Array	No	Search across applications	`["uuid-1", "uuid-2"]`
`states`	Array	No	Filter by process states	`["FINISHED", "STARTED"]`
`processStartDateAfter`	String	No	Include processes after date	`"2024-01-01T00:00:00Z"`
`processStartDateBefore`	String	No	Include processes before date	`"2024-12-31T23:59:59Z"`

Basic search parameters

searchKey (String)

value (String)

searchKeys (Array)

Purpose: Array of key-value pairs for multi-field searches with AND logic.

Usage: All conditions must match for a result to be returned.

Format:

[
  {"key": "field.path.1", "value": "value1"},
  {"key": "field.path.2", "value": "value2"}
]

Example:

[
  {"key": "application.client.personalInfo.firstName", "value": "Sarah"},
  {"key": "application.client.business.industry", "value": "Technology"}
]

Cannot be used together with searchKey. Choose one approach.

Filtering parameters

processDefinitionNames (Array)

applicationIds (Array)

states (Array)

Date range parameters

processStartDateAfter (String)

processStartDateBefore (String)

Process states explained

Understanding process states is crucial for effective searching:

State	Description	When to Use
CREATED	Process instance exists but hasn’t started execution	Rarely used for business searches
STARTED	Process is actively running	Find ongoing processes, current workload
FINISHED	Process completed successfully	Most common for business data searches
FAILED	Process encountered an error	Error analysis, troubleshooting
TERMINATED	Process was manually cancelled	Audit trails, cancelled applications
ONHOLD	Process is paused/waiting	Active cases needing attention

Recommendation: Use ["FINISHED"] for most business searches to ensure you’re getting complete, reliable data.

Response structure

The search returns a JSON object with these fields:

result (Array): List of matching process instances, automatically sorted by processStartDate in descending order (newest first)
- processInstanceUUID: Unique process identifier
- state: Current process state
- processStartDate: When the process started
- data: The actual process data with your searchable fields
tooManyResults (Boolean): True if more than 50 results found (limit applied)
success (Boolean): Whether the search completed successfully
errorMessage (String): Error details if search failed

Use cases & examples

HR employee lookup

Search for employees by department, position, or location across HR systems.

Compliance Auditing

Locate specific transactions or approvals for regulatory compliance.

Business Intelligence

Analyze process data patterns and generate reports.

Real-world example: Customer support search

Customer calls with issue

Support agent needs to find customer’s account quickly.

Search by multiple criteria

{
  "searchKeys": [
    {"key": "customer.email", "value": "customer@email.com"},
    {"key": "customer.status", "value": "Active"}
  ],
  "processDefinitionNames": ["customer_onboarding"],
  "states": ["FINISHED"]
}

Get comprehensive results

Receive full customer profile with account details, order history, and support tickets.

Resolve customer issue

Use the retrieved data to address the customer’s concern effectively.

Best practices

Performance optimization

Data Modeling

Security & Compliance

Error Handling

Troubleshooting

No Search Results

Search Timeout Errors

Invalid Search Key Errors

Connection Issues

Configuration templates

{
  "searchKey": "your.field.path",
  "value": "search_value",
  "processDefinitionNames": ["your_process"],
  "states": ["FINISHED"]
}

Elasticsearch setup

Configure Elasticsearch indexing for FlowX Engine

Data search service setup

Complete deployment and configuration guide

Process designer

Learn how to design processes with searchable data

On this page

Prerequisites
Quick start
1. Set up your data process
Configure Field Indexing
2. Create your search process
3. Configure search parameters
4. Handle search results
Search parameters reference
Quick reference table
Basic search parameters
Filtering parameters
Date range parameters
Process states explained
Response structure
Use cases & examples
Real-world example: Customer support search
Best practices
Troubleshooting
Configuration templates
Related resources

The Data Search service enables you to find specific data across process instances within your FlowX.AI platform. It uses Elasticsearch to perform fast, indexed searches across process data.

Simple Search

Search by a single field and value

Advanced Search

Search using multiple criteria simultaneously

Cross-Application

Search across multiple applications

Date Filtering

Filter results by process creation dates

Prerequisites

Before using the Data Search service, ensure you have:

Elasticsearch Configuration

Kafka Topics

Process Data

Quick start

Set up your data process

Create a process that stores searchable data and configure field indexing.

Create a search process

Build a process with Kafka Send/Receive actions for search functionality.

Configure search parameters

Define your search criteria using simple or advanced syntax.

Handle search results

Process the returned data and display results to users.

1. Set up your data process

First, create a process that contains searchable data. Add a Service Task with a business rule:

output.put("application", {
  "client": {
    "personalInfo": {
      "firstName": "Sarah",
      "lastName": "Johnson", 
      "email": "sarah.johnson@techcorp.com",
      "phone": "+1-555-0101"
    },
    "address": {
      "country": "USA",
      "city": "San Francisco", 
      "state": "California",
      "zipCode": "94102"
    },
    "business": {
      "company": "TechCorp Inc",
      "industry": "Technology",
      "position": "CTO"
    },
    "account": {
      "type": "Premium",
      "status": "Active",
      "riskLevel": "Low"
    }
  }
});

Critical Step: After creating your data structure, you must configure field indexing in Process Settings → Data Search for the search to work.

Configure Field Indexing

Navigate to Process Settings → Data Search and add the field paths you want to search:

Fields that we indexed in our example:

application.client.personalInfo.firstName
application.client.personalInfo.lastName
application.client.personalInfo.email

2. Create your search process

Create a new process with a Send Message Task:

Configuration:

Action Type: Kafka Send Action
Topic: KAFKA_TOPIC_DATA_SEARCH_IN

3. Configure search parameters

Choose your search approach based on your needs:

Use when searching by a single field:

{
  "searchKey": "application.client.personalInfo.lastName",
  "value": "Johnson",
  "processDefinitionNames": ["client_process"],
  "states": ["FINISHED"]
}

Use when searching by a single field:

{
  "searchKey": "application.client.personalInfo.lastName",
  "value": "Johnson",
  "processDefinitionNames": ["client_process"],
  "states": ["FINISHED"]
}

Use when searching by multiple criteria (AND logic):

{
  "searchKeys": [
    {"key": "application.client.personalInfo.firstName", "value": "Sarah"},
    {"key": "application.client.personalInfo.lastName", "value": "Johnson"}
  ],
  "processDefinitionNames": ["client_process"],
  "states": ["FINISHED"]
}

All conditions in searchKeys must match for a result to be returned.

Search across multiple applications:

{
  "searchKey": "application.client.account.type",
  "value": "Premium",
  "applicationIds": [
    "app-1-uuid",
    "app-2-uuid"
  ]
}

Filter by process creation dates:

{
  "searchKey": "application.client.business.industry",
  "value": "Technology",
  "processStartDateAfter": "2024-01-01T00:00:00Z",
  "processStartDateBefore": "2024-12-31T23:59:59Z",
  "states": ["FINISHED"]
}

4. Handle search results

Add a Receive Message Task with:

Data Stream: KAFKA_TOPIC_DATA_SEARCH_OUT

Success response example:

{
  "result": [
    {
      "processInstanceUUID": "b743ac99-4029-4b93-9ac3-4a45b4a62673",
      "state": "FINISHED",
      "processStartDate": "2025-05-28T12:18:50.532Z",
      "data": {
        "application": {
          "client": {
            "personalInfo": {
              "firstName": "Sarah",
              "lastName": "Johnson"
            }
          }
        }
      }
    }
  ],
  "tooManyResults": false,
  "success": true
}

Search parameters reference

Quick reference table

Parameter	Type	Mandatory	Description	Example
`searchKey`	String	Yes	Single field path to search	`"application.client.personalInfo.lastName"`
`value`	String	Yes	Value to search for (with searchKey)	`"Johnson"`
`searchKeys`	Array	Yes (if multiple fields)	Multiple field-value pairs (AND logic)	`[{"key": "field1", "value": "val1"}]`
`processDefinitionNames`	Array	Yes	Limit to specific processes	`["client_onboarding"]`
`applicationIds`	Array	No	Search across applications	`["uuid-1", "uuid-2"]`
`states`	Array	No	Filter by process states	`["FINISHED", "STARTED"]`
`processStartDateAfter`	String	No	Include processes after date	`"2024-01-01T00:00:00Z"`
`processStartDateBefore`	String	No	Include processes before date	`"2024-12-31T23:59:59Z"`

Basic search parameters

searchKey (String)

value (String)

searchKeys (Array)

Purpose: Array of key-value pairs for multi-field searches with AND logic.

Usage: All conditions must match for a result to be returned.

Format:

[
  {"key": "field.path.1", "value": "value1"},
  {"key": "field.path.2", "value": "value2"}
]

Example:

[
  {"key": "application.client.personalInfo.firstName", "value": "Sarah"},
  {"key": "application.client.business.industry", "value": "Technology"}
]

Cannot be used together with searchKey. Choose one approach.

Filtering parameters

processDefinitionNames (Array)

applicationIds (Array)

states (Array)

Date range parameters

processStartDateAfter (String)

processStartDateBefore (String)

Process states explained

Understanding process states is crucial for effective searching:

State	Description	When to Use
CREATED	Process instance exists but hasn’t started execution	Rarely used for business searches
STARTED	Process is actively running	Find ongoing processes, current workload
FINISHED	Process completed successfully	Most common for business data searches
FAILED	Process encountered an error	Error analysis, troubleshooting
TERMINATED	Process was manually cancelled	Audit trails, cancelled applications
ONHOLD	Process is paused/waiting	Active cases needing attention

Recommendation: Use ["FINISHED"] for most business searches to ensure you’re getting complete, reliable data.

Response structure

The search returns a JSON object with these fields:

result (Array): List of matching process instances, automatically sorted by processStartDate in descending order (newest first)
- processInstanceUUID: Unique process identifier
- state: Current process state
- processStartDate: When the process started
- data: The actual process data with your searchable fields
tooManyResults (Boolean): True if more than 50 results found (limit applied)
success (Boolean): Whether the search completed successfully
errorMessage (String): Error details if search failed

Use cases & examples

HR employee lookup

Search for employees by department, position, or location across HR systems.

Compliance Auditing

Locate specific transactions or approvals for regulatory compliance.

Business Intelligence

Analyze process data patterns and generate reports.

Real-world example: Customer support search

Customer calls with issue

Support agent needs to find customer’s account quickly.

Search by multiple criteria

{
  "searchKeys": [
    {"key": "customer.email", "value": "customer@email.com"},
    {"key": "customer.status", "value": "Active"}
  ],
  "processDefinitionNames": ["customer_onboarding"],
  "states": ["FINISHED"]
}

Get comprehensive results

Receive full customer profile with account details, order history, and support tickets.

Resolve customer issue

Use the retrieved data to address the customer’s concern effectively.

Best practices

Performance optimization

Data Modeling

Security & Compliance

Error Handling

Troubleshooting

No Search Results

Search Timeout Errors

Invalid Search Key Errors

Connection Issues

Configuration templates

{
  "searchKey": "your.field.path",
  "value": "search_value",
  "processDefinitionNames": ["your_process"],
  "states": ["FINISHED"]
}

Elasticsearch setup

Configure Elasticsearch indexing for FlowX Engine

Data search service setup

Complete deployment and configuration guide

Process designer

Learn how to design processes with searchable data

On this page

Prerequisites
Quick start
1. Set up your data process
Configure Field Indexing
2. Create your search process
3. Configure search parameters
4. Handle search results
Search parameters reference
Quick reference table
Basic search parameters
Filtering parameters
Date range parameters
Process states explained
Response structure
Use cases & examples
Real-world example: Customer support search
Best practices
Troubleshooting
Configuration templates
Related resources

Simple Search

Advanced Search

Cross-Application

Date Filtering

​Prerequisites

​Quick start

​1. Set up your data process

​Configure Field Indexing

​2. Create your search process

​3. Configure search parameters

​4. Handle search results

​Search parameters reference

​Quick reference table

​Basic search parameters

​Filtering parameters

​Date range parameters

​Process states explained

​Response structure

​Use cases & examples

HR employee lookup

Compliance Auditing

Business Intelligence

​Real-world example: Customer support search

​Best practices

​Troubleshooting

​Configuration templates

​Related resources

Elasticsearch setup

Data search service setup

Process designer

Microservices

Plugins

Observability

Microservices access rights

Plugins access rights

Simple Search

Advanced Search

Cross-Application

Date Filtering

​Prerequisites

​Quick start

​1. Set up your data process

​Configure Field Indexing

​2. Create your search process

​3. Configure search parameters

​4. Handle search results

​Search parameters reference

​Quick reference table

​Basic search parameters

​Filtering parameters

​Date range parameters

​Process states explained

​Response structure

​Use cases & examples

HR employee lookup

Compliance Auditing

Business Intelligence

​Real-world example: Customer support search

​Best practices

​Troubleshooting

​Configuration templates

​Related resources

Elasticsearch setup

Data search service setup

Process designer

Prerequisites

Quick start

1. Set up your data process

Configure Field Indexing

2. Create your search process

3. Configure search parameters

4. Handle search results

Search parameters reference

Quick reference table

Basic search parameters

Filtering parameters

Date range parameters

Process states explained

Response structure

Use cases & examples

Real-world example: Customer support search

Best practices

Troubleshooting

Configuration templates

Related resources

Prerequisites

Quick start

1. Set up your data process

Configure Field Indexing

2. Create your search process

3. Configure search parameters

4. Handle search results

Search parameters reference

Quick reference table

Basic search parameters

Filtering parameters

Date range parameters

Process states explained

Response structure

Use cases & examples

Real-world example: Customer support search

Best practices

Troubleshooting

Configuration templates

Related resources