Frends iPaaS Roadmap

A completely new Frends web application that is deployed alongside the main Frends User Interface that is meant to provide a unified API Developer on-boarding and discoverability experience to both internal and external API consumers.

The API portal will support the following use cases and features:

• API Consumer registration and on-boarding

  • Utilizing an identity management system chosen by the customer

• API Products

  • Create and manage API Products in the API Portal that are available to be consumed by the API users

  • API Products are a combination of existing API’s either directly in Frends or managed as passthrough API’s using the Frends Passthrough API Management functionality

• API Discoverability

  • Publish API Products you have configured using the API Portal

• Lightweight CMS

  • Create API marketing and help content using markdown to publish on the API Portal

• Whitelabeling

  • Enable customers and partners to provide lightweight whitelabelling customizations to change for eg. fonts, colors, logos and so on.

An extension to current Frends functionality which allows multiple Frends processes to be chained together in the same process definition by configuring an identification or correlation variables that links the independent process parts together.

An example long-running process functional description:

Process Part 1:

• Triggered with a schedule

• Retrieve a file from an SFTP server

• Write file to a local folder

• Save OrderID to be the correlation ID of the long-running process

• OrderID is parsed from the file name transferred with the SFTP transfer

Process Part 2:

• Establish a file trigger that looks for a fille with the same OrderID present in a different folder

• Read in the new file and transfer it to a separate SFTP server

• Any amount of time can pass between Process Parts 1 and 2.

Key Enhancements:

• Timer BPMN Shape

  • A new BPMN Shape in the Process Editor to stop the execution of a process for a predetermined period of time.

• Wait For Signal BPMN Shape

  • A new BPMN Shape in the Process Editor to stop the execution of a process awaiting for an external signal to continue

  • This signal can come from within the same integration process or from another integration process entirely

  • This will allow also for logical chaining of integration processes

• Send Signal BPMN Shape

  • A new BPMN Shape in the Process Editor to continue the execution of a specified integration process and it's specific stopped instance

• Stateful and Persisted Process

  • All of the data processed within the integration flow can be fully persisted during the wait functionalities described above allowing for fully stateful processes

We are proud to announce the second iteration of our overall low-code approach in Frends, that builds on our existing success with the ease of use as well as flexibility of our current low-code configuration capabilities.

Key Enhancements:

• Automatic Data Schema Detection

  • With this feature, users will be able to provide arbitrary data during development, which will be used to determine the lineage of the data as well as the schema of the data to enable a fully qualified intellisense experience when utilizing low-code references. This also enables all current Frends' Tasks to provide a fully working intellisense schema support fully automatically for an even easier development experience.

• Support For Complex Loops

  • This will enable users to iterate through complicated arrays or collections of their data whilst creating low-code configurations without the need for writing additional C# code for the functionality. This means that creating complex messages has never been easier.

• Support For IF/ELSE

  • This will enable users to create natively supported IF/ELSE statements directly into their low-code references to allow users to better deal with missing data or complex data mapping use cases with interconnected dependencies without the need for writing additional C# code for the functionality.

• Intuitive Syntax

  • All of the low-code reference improvements will follow a similar double handlebars ("") syntax users are already familiar with to allow for a more seamless adoption of the enhancements into the daily usage by our users.

After many hundreds of votes and customer requests, Frends is finally implementing a visual data mapper to enable users more intuitive and easier way to transform data between any two formats or schemas.

Key Enhancements:

• Automatic Data Schema Detection

  • With this feature, users will be able to provide any structured data for the Visual Data mapper which will infer the underlining schema of the data to allow for easy drag-and-drop mapping of different fields and handle their types correctly

• AI Assisted

  • The Visual Data Mapper will include an AI Assistant that will allow users to ask the AI to create the mapping between two provided data structures automatically.

• Supports Low-Code:

  • The Visual Data Mapper will include the capability to utilize existing Low-Code C# functionality of Frends to further manipulate and process data during the mapping process.

This set of features enables Frends to act as the "toolbox" for Autonomous AI Agents, which are an emerging technology over the next 12 to 24 months. These autonomous AI Agents will be capable of replacing humans in various day-to-day tasks such as customer service, sales, operative management, data processing and so on.

In order for any given organization to be able to take full advantage of these emerging AI Agents, the organization will need to be able to provide said AI Agents access to their existing business processes, systems and data in a seamless and well governed way.

Key Enhancements:

• Orchestrate AI Access to Systems

  • With Frends' existing best in class business process orchestration capabilities users will be able to package sections or entire business processes as tools offered for the AI Agents to use.

• AI Toolbox Packaging

  • Frends will also attach additional business architecture oriented documentation about above mentioned business processes or their sections to allow the AI Agents to understand how and when they should utilize which tool to achieve their goals.

• Open API  Based Access

  • With the newly renewed API Management features of Frends, Frends will be able to offer technically compliant, well governed, monitored and secure access for the AI Agents to practically consume these pacakged AI tools in the form of Open API calls. This will also serve as a crucial component of AI TRiSM capabilities where you can also protect your business processes and systems from unwanted AI usage.

• Automatic Toolbox Lifecycle Management

  • To top everything off Frends will be able to utilize all of the above to automatically publish any changes to your system or business process landscape avoiding costly system changes or complex re-configuring of AI Agents.

Frends will later release our initial list of supported AI Agent models later in 2025.

Additionally see our webinar on this specific topic at https://frends.com/webinar/will-your-business-sink-or-swim-in-the-next-ai-wave.

For more information about Autonomous AI Agents see the following Gartner research: https://www.gartner.com/en/articles/intelligent-agent-in-ai

The next item on Frends' AI Enablement journey is the Frends LLM Process Intelligence AI, to enable users to create BPMN 2.0 compliant processes with NLP interaction with the user. This feature set fully builds on the AI Augmented developer experience of previous Frends LLM features.

Key Enhancements:

• NLP Based Visual Process Definition

  • Users can ask the Processes Intelligence AI to create a framework for an integration flow or a business process they wish to automate using BPMN 2.0 notation.

• Draw On Best Practices

  • The Process Intelligence AI is able to tap into the wealth of knowledge and best practices developed with Frends over the years to avoid common pitfalls as well as have the AI create processes that follow accepted best practices for any vertical or horizontal solution.

• Fine-Tuning with Additional Prompts

  • After receiving the initial response, users have the flexibility to provide additional prompts to further refine and customize the generated description.

This feature will enhance Frends' current capabilities to integrate external AI Models into their integration processes by introducing various security, developer productivity and other enhancements alongside with the current capabilities.

Key Enhancements:

• Record All AI Traffic

  • Stores all AI Related traffic for monitoring and audit trail purposes inside Frends

• Limit AI Usage With RBAC

  • Configure user role based limits on what AI Models are available for use and what kind of prompts are allowed

• Detect AI Misuse

  • Configure rules to detect incorrect or inappropriate use of AI within Frends such as denying processing of personally identifiable information

• Fine Tune Models

  • Allows developers to finetune their prompts and RAG prompting directly from within Frends

• AI Response Analysis

  • Allows users to flag desired AI responses of behaviours as correct and undesired behaviour as incorrect to automatically fine tune the usage of the AI for future use cases

Passthrough APIs provide a way of more easily configure API calls to be forwarded to backend system and ways of monitoring these calls

• Passthrough API functionality to enable users to easily configure existing API’s to be governed by Frends API Management without having to have an underlining Frends process attached to the API.

  • The passthrough API will have simplified configuration capabilities to modify:

    • HTTP Headers

    • Authentication methods

    • URL paths and parts

• Improved API Monitoring capabilities

  • Introduce new API Monitoring views to show more API relevant data such as HTTP response codes as well as better ways to view the overall API health and execution statistics

API Policies

We are introducing Unified API Policies, designed to centralize and streamline access management for all API’s while preparing for the upcoming release of the Frends API Portal.

Key Enhancements:

• Unified Policy Configuration: With Unified API Policies, you can easily configure access restrictions and throttling for all your APIs through a single, user-friendly mechanism.

• Throttling and Access Control: Tailor API Policies to meet your specific needs. Define access limits and throttling rules to ensure optimal API usage and prevent abuse.

• Adaptable to Any Authentication Method: API Policies are versatile and can be applied to APIs regardless of the authentication method used, providing consistent control and management.

New Authentication Method: Private Application Registration

Additionally we are introducing a new authentication method to work with the reworked API Policies: Private Application Registrations.

Key Enhancements:

• Secure Authentication: Private Application Registrations supersede API Keys, offering a more secure and modern authentication solution.

• Static JWT Tokens: These tokens are essentially static JSON Web Tokens (JWT) containing user-provided data about the API consumer, alongside digital signatures to ensure data integrity.

We are introducing an advanced feature within Frends that enables users to create Code shapes efficiently through natural language prompts. This enhancement streamlines the process of writing C# code to perform complex integration tasks within your integration processes.

Key Enhancements:

• Contextual Information: System prompts are integrated to provide contextual details for process configuration, including environment variable names, process variables, trigger variables, and access to task results.

• Seamless Integration: When opted in the Process Editor seamlessly connects to our LLM service (Azure Open AI) for effortless use.

• Tenant-Specific Configuration: For security and flexibility, each Frends tenant will utilize it’s own dedicated instance of the LLM model for context and session security.

We are introducing a powerful new capability within Frends that enables users to generate process descriptions and documentation with ease, using the Frends Large Language Model (LLM). This feature simplifies the process of creating detailed descriptions for your Processes.

Key Highlights:

• Description Creation: Users can initiate the process by simply clicking a button to have the Frends LLM generate an initial Process description and documentation based on the BPMN Process designed, variables and Tasks used as well as any user provided documentation.

• Fine-Tuning with Additional Prompts: After receiving the initial response, users have the flexibility to provide additional prompts to further refine and customize the generated description.

Building on the previous feature of LLM Code Generation we are also introducing a feature that allows users to configure Tasks seamlessly through natural language prompts. This simplifies the process of configuring Task parameters, creating low-code mapping configurations and utilizing Task results and other variables when configuring Frends tasks.

Key Highlights:

• Effortless Task Configuration: Users can effortlessly configure Tasks by describing the required functionality for the task using plain language, eliminating the need for manual configuration.

• Contextual Continuity: This feature retains the chat context, enabling users to iteratively enhance Task configurations within the same conversation as well as test out their configuration at any time.

• Tenant-Specific Configuration: For security and flexibility, each Frends tenant will utilize it’s own dedicated instance of the LLM model for context and session security.

We are introducing a valuable enhancement to the Frends Process Editor by incorporating Decision Model and Notation (DMN) functionality. DMN provides an efficient means of mapping data and decision-making, as described in detail here.

Key Enhancements:

• DMN Shape Integration: With this feature, we are introducing a dedicated DMN shape within the Frends Process Editor. This shape will allow users to create input maps following the table structure outlined in the Wikipedia article.

• Mapping to Frends Variables: Users can easily associate DMN inputs with various Frends variables, streamlining the data mapping process.

• Output Generation: The result of the DMN shape will provide corresponding outputs based on the input configurations ready to be used in following integration tasks and steps.