Latest features, improvements, and bug fixes in our newest release
This release includes the following features in Tech Preview. We encourage you to try them out and share your feedback to help us improve them. Please note that Tech Preview features may change before final release.
FlowX.AI 5.0 introduces Workspaces, enabling organizations to manage multiple business lines, verticals, or countries within a single FlowX.AI instance while maintaining complete data isolation.
Multi-Tenant Architecture
Logical separation of business contexts with shared infrastructure
Enhanced Access Control
Role-based access control (RBAC) and Access Control Lists (ACLs) with workspace-specific permissions
Data Isolation
Complete logical isolation between workspaces while enabling controlled resource sharing
User Groups & Roles
Simplified permission management through groups and workspace-specific roles
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Accelerated Onboarding
Onboard new business verticals in days instead of weeks with shared platform capabilities
2
Enhanced Governance
Implement fine-grained access control with workspace-specific roles and permissions
3
Operational Efficiency
Centralize platform upgrades, maintenance, and monitoring across all business units
Multi-National Operations
Separate workspaces for different countries/regions with shared global processes
Business Unit Separation
Independent workspaces for retail, corporate, and investment banking divisions
Regulatory Compliance
Isolate processes subject to different regulatory requirements
Team-Based Development
Enable different teams to work independently while sharing common resources
Major Infrastructure Changes: Workspaces introduces SpiceDB integration and new database schemas for multi-tenant architecture.
Key Changes:
SpiceDB Integration: New permission management system requiring deployment
Database Migration: Schema updates for workspace support
User Storage: Only information about FlowX.AI Designer users is stored in FlowX.AI. The stored user data is limited to: unique identifier, username, first name, last name, and email address.
Default Workspace: All the projects and libraries are migrated to default workspace
Backward Compatibility: All existing functionality preserved in default workspace
New Login Flow: After authentication, select your workspace before accessing FlowX.AI Designer. Once inside a workspace, everything works as before.
What’s New:
Workspace Selection: Choose workspace after login
Resource Isolation: Projects, libraries, themes are workspace-specific
Enhanced Permissions: Fine-grained access control with user groups and ACLs
Workspace Management: Create and manage workspaces (admin users)
What Stays the Same:
Process design and configuration
UI Designer capabilities
Integration patterns
All existing FlowX.AI Designer features
Strategic Transformation: Workspaces enables enterprise multi-tenant architecture with independent business unit governance while sharing platform capabilities.
Business Impact:
Faster time-to-market for new business verticals
Enhanced compliance with workspace-specific controls
Improved governance with fine-grained access management
Enterprise Benefits:
Business unit autonomy with shared platform
Regulatory compliance through data isolation
Centralized upgrades and maintenance
Cross-business unit resource sharing when appropriate
The new Project Data Model feature enables you to define and manage data types at the project level, which can then be reused across all processes within your project.
Centralized Management
Define data types once at the project level and reuse them across multiple processes
Automatic Propagation
Changes to PDM data types automatically propagate to all referencing processes
Enhanced Governance
Configure sensitive data and reporting settings at the project level
Library Integration
Use data types from libraries in your Project Data Model
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Reduce duplicate work
Define common data types like Customer, Product, or Document once instead of recreating them in each process
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Simplify maintenance
Update a data type in one place and have changes apply everywhere it’s used
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Standardize data structures
Enforce consistent naming, structure, and governance across your application
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Accelerate development
Create new processes faster by leveraging pre-defined data types
Infrastructure Impact: PDM has minimal infrastructure impact - it’s a design-time feature that improves development efficiency without affecting runtime resources.
No deployment changes required - PDM is part of the design platform, not runtime
Backward compatible - Existing processes continue to work unchanged
Game Changer: Define data types once at project level, use everywhere. No more recreating Customer or Order objects in every process.
How to Use PDM:
Navigate to Project → Config → Data Model
Define your business entities (Customer, Product, etc.)
Set governance rules (sensitive data, reporting)
Use these types in any process within the project
Best Practices:
Start with core business entities
Use clear, consistent naming
Mark sensitive fields appropriately
Leverage library data types when available
Strategic Value: PDM transforms how your organization manages business data definitions. Define business entities once and ensure consistency across all processes and teams.
Business Benefits:
Enhanced compliance through centralized governance and data sensitivity controls
Reduced errors from consistent data definitions
ROI Indicators:
Development Efficiency: Measure reduction in process creation time
Error Reduction: Track fewer data-related production issues
Maintenance Cost: Monitor time spent on data structure updates
FlowX.AI Database is a new persistence layer that enables you to store and retrieve data across different processes and applications, without relying on external systems.
Data Persistence
Store data that persists beyond process instances
MongoDB Operations
Find, insert, and manipulate data using familiar MongoDB operations
Workflow Integration
Seamlessly integrate with workflows through Data Source nodes
Document Collections
Organize your data in structured collections
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Share data between processes
Enable communication and data sharing between different process instances
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Reduce external dependencies
Store operational data within FlowX.AI instead of building custom connectors
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Enable new use cases
Build dashboards, caching solutions, and other applications that require persistent data
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Simplify architecture
Keep your data within the FlowX.AI ecosystem for improved security and simplicity
FlowX.AI Database as a Data Source type
FlowX.AI Database integrates directly into the existing Integration Designer as a new Data Source type alongside RESTful System, making it easy to create and manage database collections without learning new interfaces.
Infrastructure Planning Required: FlowX.AI Database creates additional MongoDB collections and requires infrastructure planning for storage, monitoring, and backup procedures.
New microservice: NoSQL DB Runner. Check the setup guide for more details.
Key Considerations:
Storage Planning: Monitor usage as processes adopt internal database (plan for 20-30% increase)
Performance Monitoring: Set up alerts for FlowX.AI Database query performance
Backup Strategy: Include FlowX.AI Database collections in backup procedures
Connection Pooling: Additional connection pools for database operations
Memory: Additional 256MB-512MB per FlowX.AI instance for database operations
New Integration Option: FlowX.AI Database appears as a new Data Source type in Integration Designer, right alongside RESTful System.
When to Use FlowX.AI Database:
Customer data lookup across processes
Shared configuration and reference data
Process-to-process communication
Caching frequently accessed data
Temporary operational data storage
How to Implement:
Add Data Source node to your process
Select “FlowX.AI Database” as type
Configure collection and operations
Use familiar MongoDB syntax (find, insert, update)
When NOT to Use: Don’t replace your core business systems. FlowX.AI Database is perfect for operational data, caching, and inter-process communication - but your CRM, ERP, and other systems of record should remain your primary data sources.
Strategic Value: FlowX.AI Database enables new operational patterns that were previously complex or impossible. It’s not about replacing your core systems, but about enabling new ways to orchestrate business processes.
New Business Capabilities:
Cross-process workflows: Loan application → Credit check → Approval across different process instances
Real-time dashboards: Operational data for business monitoring without system integration
Agile experimentation: Test new business rules without impacting core systems
Process orchestration: Complex business flows spanning multiple departments
ROI Considerations:
Time to Market: Faster implementation of new business processes
Agility: Rapid prototyping and testing of business ideas
Use FlowX.AI Database when:
Data is operational and process-specific (not master data)
You need rapid implementation without IT system changes
Process instances need to communicate with each other
The new Multi Select component allows users to choose multiple options from a predefined list, expanding upon the existing single Select component to support multi-value scenarios.
Multiple Selections
Users can select multiple options from dropdown lists, with values stored as arrays
Flexible Display Options
Show selections as chips, comma-separated lists, or custom formats
Selection Limits
Configure maximum number of selectable options to control user input
Search & Filter
Built-in search functionality to filter through large option lists
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Skills & Competencies
Allow users to select multiple skills, qualifications, or areas of expertise
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Categories & Tags
Enable selection of multiple categories, tags, or classification options
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Product Features
Let customers choose multiple product features, services, or add-ons
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Preferences & Settings
Capture user preferences where multiple options can be active simultaneously
Multi Select configuration options
Configure Multi Select components with the same ease as other form elements. Set maximum selections, display formats, search options, and validation rules through the familiar UI Designer interface.
Key Configuration Options
Max. Options Selectable: Limit the number of selections
Show selections: Choose how selected items are displayed
Search for options: Enable filtering within large lists
Has Clear: Allow users to clear all selections at once
No Infrastructure Impact: Multi Select is a pure UI component with no backend requirements. It works with existing form handling and data storage mechanisms.
Zero deployment overhead - Component is part of the UI framework upgrade
Existing data handling - Uses standard array storage, no schema changes needed
Easy Integration: Multi Select works just like other form elements in UI Designer. Drag, drop, configure - no new learning curve required.
Common Use Cases:
Skills Selection: Job applications, team member profiles, contractor skills
Product Features: Insurance coverage options, software licensing features
User Experience Impact: Multi Select eliminates user frustration in scenarios where single selection doesn’t match real-world needs. This improves data quality and user satisfaction.
Before vs After:
❌ Before: “I can only select one skill, but I have multiple certifications”
✅ After: “Perfect! I can select all my relevant skills at once”
Business Process Examples:
Employee Onboarding: Select multiple skills, certifications, department access
Product Configuration: Select multiple features, add-ons, support packages
Customer Preferences: Select multiple communication channels, product interests
Analytics Benefit: Multi-select data provides richer analytics. Instead of knowing a customer chose “Primary Interest: Technology,” you know they selected “AI, Cloud Computing, Cybersecurity, Mobile Development” - much more actionable for business intelligence.
FlowX.AI 5.0 introduces the ability for libraries to depend on other libraries, enabling hierarchical dependency structures and more sophisticated modular architectures.
Hierarchical Structure
Create complex dependency trees with multiple levels of library-to-library relationships
Resource Inheritance
Projects automatically gain access to resources from the entire dependency hierarchy
Version Control
Single-version constraint ensures consistency across the dependency tree
Conflict Prevention
Built-in validation prevents circular dependencies and version conflicts
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Enhanced Modularity
Break down complex functionality into smaller, focused libraries that can depend on each other
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Team-based Development
Enable different teams to own and maintain specific libraries while building on shared foundations
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Specialized Libraries
Create country-specific or domain-specific libraries that extend common base libraries
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Simplified Architecture
Organize libraries hierarchically, reducing complexity and improving maintainability
Example dependency tree with library-to-library dependencies
In this example, both Integrations Library and Subprocesses Library depend on other libraries, creating a multi-level hierarchy that the Mortgage Project can leverage.
Full Backwards Compatibility: FlowX.AI 5.0 maintains full backwards compatibility with existing project-to-library dependencies from FlowX.AI 4.x. All existing dependencies will continue to work without modification.
Upgrade Process:
Existing dependencies will be automatically migrated
New library dependency features become available immediately
No breaking changes to existing functionality
Enhanced validation may catch previously undetected issues
Post-Migration Required: After the lib2lib migration is executed, you must clear the cache. This is necessary because a new field is added to the build mongo document.
Cache Clearing Steps:
Complete the lib2lib migration process
Clear the application cache to ensure the new build document fields are properly recognized
Verify that library-to-library dependencies are functioning correctly
Key Changes:
Build Export Changes: Build exports now automatically include entire dependency trees (larger packages but self-contained)
Dependency Validation: Build process now checks for dependency conflicts (enhanced validation may catch previously undetected issues)
Enhanced Organization: You can now create more sophisticated library structures where specialized libraries build upon common foundations. This reduces duplication and improves consistency.
How It Works:
Navigate to Library → Config → Dependencies
Add other libraries as dependencies
FlowX.AI validates for conflicts automatically
Resources from all dependency levels become available
Best Practices:
Plan your library hierarchy before implementation
Keep dependencies focused and purposeful
Avoid circular dependencies
Use semantic versioning consistently
Document dependency relationships clearly
Example: Create a “US Banking Library” that depends on “Global Banking Library” and “US Compliance Library”. This way, US-specific processes get both global banking functionality and local compliance requirements automatically.
Enterprise Architecture: Library-to-Library Dependencies enable sophisticated organizational structures where different teams can own specific business domains while building on shared foundations.
Enterprise Use Cases:Multi-Country Operations:
Global Insurance Company: US-specific library depends on Global Compliance library
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US Insurance Library → Global Compliance Library → Base Insurance Library
Product Line Specialization:
Bank: Mortgage processes use specialized libraries that extend common banking operations
Change Management: This capability requires coordination between teams. Establish clear ownership models, communication protocols, and upgrade procedures before implementing complex dependency hierarchies.
Data Mappers enable users to visually map data transfers between components with intuitive drag-and-drop functionality while maintaining full backward compatibility with existing implementations.
Visual Data Mapping
Drag-and-drop interface for mapping data between source and destination components
Component Integration
Seamlessly connect processes, subprocesses, workflows, and business rules
Parameter Management
Define input/output parameters with predefined and flexible parameter types
Backward Compatibility
Choose between new Data Mapper or existing implementation methods
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Simplified Integration
Visual interface eliminates complex configuration syntax and reduces integration errors
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Enhanced Reusability
Define parameters once and reuse across multiple components and processes
3
Improved Governance
Centralized parameter management with clear data flow visibility
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Zero Migration Risk
Optional adoption with full backward compatibility ensures smooth transition
Call Activity Mapping
Map data between parent processes and subprocesses (sync/async)
Integration Workflows
Connect processes with Integration Designer workflows
Business Rules
Pass data to and from business rule executions
Node-to-Node Data Flow
Map data between workflow nodes (REST endpoints, data persistence)
Zero Infrastructure Impact: Data Mappers is a design-time feature that enhances the FlowX.AI Designer interface without requiring additional infrastructure or deployment changes.
Full Backward Compatibility: All existing data transfer mechanisms (like append to parent process or output.[outputKey]) continue to work unchanged. Teams can adopt Data Mappers at their own pace.
Key Points:
No new microservices - Enhancement to existing designer interface
No runtime changes - Data mapping occurs at design time
Existing configurations preserved - Zero impact on current implementations
Optional adoption - Teams choose when and where to use new functionality
Game Changer for Integration: No more complex syntax for data transfers. Visual drag-and-drop interface makes component integration intuitive and error-free.
How to Use Data Mappers:
Define Parameters: Set input/output parameters on Start/End nodes
Choose Implementation: Select “Data Mapper” or “Current” method
Visual Mapping: Drag source parameters to destination parameters
Save Configuration: Store mappings for reuse and maintenance
When to Use:
Call Activities: Passing data between parent and child processes
Integration Workflows: Connecting with external systems
Complex Data Flows: When visual mapping improves clarity
Team Collaboration: When multiple people work on integration logic
Parameter Changes: When you modify input/output parameters, existing mappings must be manually updated. Changes don’t automatically propagate to avoid unintended data flow modifications.
Strategic Value: Data Mappers transforms technical integration tasks into visual, business-friendly workflows. Non-technical stakeholders can now understand and validate data flows between business processes.
Business Impact:
Reduced Errors: Visual mapping prevents data integration mistakes that cause process failures
Faster Development: Intuitive interface accelerates process configuration and testing
Better Documentation: Visual data flows serve as living documentation of business logic
Team Collaboration: Business and technical teams can discuss data flows using the same visual interface
ROI Indicators:
Development Speed: Measure reduction in integration configuration time
Error Rate: Track fewer data-related production issues
Team Efficiency: Monitor cross-functional collaboration improvements
Process Quality: Assess improvement in first-time-right deployments
Use Cases by Industry:
Banking: Loan application data flowing from customer intake → credit check → approval process
Insurance: Claim data mapping from initial report → investigation → settlement
Manufacturing: Order data flowing from sales → production planning → fulfillment
FlowX.AI 5.0 introduces Reusable Resources, a revolutionary new section that eliminates repetitive development work by enabling you to create and manage both UI Templates and Business Functions that can be used across multiple processes and projects.
Business Logic Reuse
Create JavaScript or Python functions once and use them across multiple processes via Business Rule actions
Data Model Integration
Define input/output parameters with full project data model integration and testing capabilities
Interactive Testing
Test functions with sample data in real-time before deployment to ensure accuracy
Automatic Propagation
Changes to functions automatically update all instances across your application
UI Component Reuse
Design UI components once and instantiate them across multiple User Tasks with automatic data binding
Centralized Management
Manage all templates from the new Reusable Resources section alongside Reusable Functions
Omnichannel Support
Templates work seamlessly across different platforms and channels
Flexible UI Actions
Define UI actions within templates with two scenarios: template-defined actions or form-centric data handling
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Eliminate repetitive development
Stop recreating the same business logic and UI patterns across different processes - build once, use everywhere
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End manual component updates
Update functions and templates in one place to automatically affect all instances across your application
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Centralized template management
Replace scattered, inconsistent UI patterns with centrally managed, reusable components
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Accelerate time-to-market
Build new processes faster by leveraging pre-built, tested components instead of starting from scratch
Reusable Functions Examples
Customer Data Validation Function:
Input: firstName, lastName, email, phone
Logic: Format validation, duplicate checking, data standardization
Output: validatedCustomer object with formatted data
Usage: Customer onboarding, profile updates, registration processes across all channels
Minimal Infrastructure Impact: Reusable Resources is primarily a design-time enhancement that leverages existing FlowX infrastructure with minimal additional overhead.
Infrastructure Considerations:
Execution Context: Functions execute within existing process engine contexts - no additional runtime infrastructure required
No New Microservices: Features are integrated into existing FlowX.AI platform components
Development Game Changer: Access the new “Reusable Resources” section in FlowX.AI Designer - located alongside “Reusable Functions” - to eliminate 60-80% of repetitive development work.
Key Capabilities:
Data Model Support: Full integration with Project Data Model (PDM)
Action Scenarios: Template-defined actions assigned during instantiation OR form-centric actions handled by User Task
Omnichannel: Templates work across web, mobile, and other channels
Best Practices:
Start with common patterns: Identify frequently repeated business logic and UI components
Test thoroughly: Use interactive testing for functions and preview mode for templates
Document usage: Include clear descriptions and example use cases
Revolutionary Business Impact: Reusable Resources fundamentally changes how organizations approach process development, transforming from “build every time” to “build once, leverage everywhere.”
Strategic Business Value:
Quality Assurance: Dramatic reduction in defects through reusable, tested components
Maintenance Efficiency: Update business rules once to instantly affect all processes
Team Productivity: Developers focus on new business capabilities instead of repetitive development
Consistency: Ensure uniform business rules and user experience across all touchpoints
FlowX.AI 5.0 introduces Workspaces, enabling organizations to manage multiple business lines, verticals, or countries within a single FlowX.AI instance while maintaining complete data isolation.
The new Project Data Model feature enables you to define and manage data types at the project level, which can then be reused across all processes within your project.
The new Multi Select component allows users to choose multiple options from a predefined list, expanding upon the existing single Select component to support multi-value scenarios.
FlowX.AI 5.0 introduces the ability for libraries to depend on other libraries, enabling hierarchical dependency structures and more sophisticated modular architectures.
FlowX.AI 5.0 introduces Reusable Resources, a revolutionary new section that eliminates repetitive development work by enabling you to create and manage both UI Templates and Business Functions that can be used across multiple processes and projects.
