Skip to main content

83 docs tagged with "Business Process design"

View All Tags

Add and configure Model and Dataset steps in Business Process

The Model steps (previously, AutoML Bridge) enable integrating and executing a Machine Learning (ML) model or model-related operations in a Business Process (BP). In addition to the legacy Execute AutoML Model (AutoML Bridge) step, Work.AI offers the following no-code Model steps:

Add Bot Task

Bot Tasks contain work to be done by WorkFusion's bots automating human labor. Bot Tasks can exist only as a Business Process step, and you can create them using code tools or in a no-code manner.

Add composite rules

Composite rules define a Business Process (BP) flow variant, depending on the Record column values.

Add connections

Before you can use a Business Process (BP), you must link its elements by connections, thus defining the flow of data file Records across the process steps. The arrow displays the connection direction.

Add Manual Task

To add a Manual Task (MT) to a Business Process (BP), use one of the following methods:

Add nested Business Processes

When designing a Business Process (BP), you can include another BP in it. This allows you to reuse process designs and improve BP testing, monitoring, and visualization.

Add no-code Rate Limiter step

The no-code Rate Limiter bot step enables you to control the number of records passing through the step within a specific time frame. This is particularly beneficial for implementing rate-limiting at a granular level, such as per AI Agent, reducing the impact on resources when two AI Agents are running in a single environment.

Basic concepts for Business Process implementation

A Business Process (BP) is an automation flow combining various code based and no-code elements, such as Manual Tasks, Bot Tasks, Model steps, decision or transformation rules, or nested processes. Work.AI allows you to implement two types of Business Processes (BP):

Build Business Process flow in Workflow designer

Designing a Business Process (BP) means creating and configuring a sequence of code-based or no-code steps, such as Manual or Bot Tasks, nested processes, or rules, as required to accomplish a business goal.

Build Business Process from Bot Task

The guide illustrates the implementation of a schemaless Business Process (BP) for website rating from a Bot Task using the Work.AI Developer and Control Tower capabilities. For exact steps, watch the video recording below.

Configure AI Agent

A crucial aspect of installation and further support is implementing an AI Agent (or AI Digital Worker) so that you can change any setting outside of the implementation code without recompiling, updating, or re-deploying your AI Digital Worker. Typically, this is achieved by making your configuration external to the source code.

Configure bot steps in UI

The custom bot step configuration user interface is used to simplify the specification of configuration parameters for bot steps. The feature enables the creation of complex forms using frameworks like FormIO or React and is supported for Java Native Workers (JNWs), Triggers, Bot Config Bundles (BCBs), and WebHarvest tasks.

Configure no-code Generic Connector

Using the no-code Connector step, you can apply multiple configuration options to handle different connection scenarios and create custom connectors for the integration of external services into your automations.

Connect to external database

The ODF 2 provides the built-in ORM layer and comes with OrmLite as the default ORM framework used primarily to access Data Store data.

Connectors

Connectors in the Work.AI platform enable Business Processes (BPs) and AI Agents to communicate with external systems. They provide standardized integration points for retrieving and enriching data, sending information to third-party services, triggering workflows based on external events, and orchestrating end-to-end automation across enterprise environments.

Copy Business Process

Business Processes (BP) with the same name have a common template, otherwise known as Definition. If you modify the design or parameters in one BP, the modification also affects all other instances with the same definition.

Create and manage templates

Templates are intended to simplify document ingestion by enabling automated information extraction from structured forms (for instance, ACORD). When a template is created, blank forms are annotated with labels. Based on these labels, data is then extracted from input documents.

Create Bot Task

Before getting into details, let's take a quick look at a simple Bot Task within the ODF 2 framework:

Deploy Asset Bundle

After creating an ODF 2 project from the Simple Archetype, deploy it to a Control Tower instance.

Explore Data Model

In the article, the standardized Data Store schema is understood as equivalent to the ODF 2 Example project's Data Store schema. With few exceptions, it utilizes concepts from Transaction and Multi-process layers of the ODF 2 architecture. If you do not use the Multi-process layer, you can ignore some entities, and this won't impact the framework integrity. In extreme scenarios, when even the Transaction layer is not used, the Data Store schema should be designed from scratch.

Generate ODF 2 project

Maven archetypes are templates that let you quickly generate projects from a predefined set of core files. The guide describes how to use the ODF 2 Simple Archetype to generate a new project.

Get started with Control Tower

Control Tower (CT) is the central orchestration application of the Work.AI platform. It enables users to perform the following actions:

Implement Qualification Business Process

The qualification mechanism is no longer available for access control purposes and is replaced by a new user management approach. However, to support training before employees begin performing actual tasks, WorkFusion provides a special Qualification Business Process (BP), which you can deploy and configure as described below.

Import Asset Bundle via Control Tower UI

Previously, it took a long time to transfer a Business Process with all dependencies. It required multiple operations and manual steps, in-depth model knowledge, Nexus, and s3 credentials.

Manage Data Model with Liquibase

With ODF 2, we encourage you to use Data Stores as a universal and effective way to have different steps of Business Processes within your AI Agent exchange data. The section provides a reference on how to organize your Data Model through AI Agent automation.

Manual Task

The guide explains how to add a Manual Task to a Business Process based on ODF 2. When working with Manual Tasks, consider the following aspects:

Migrate from ODF to ODF 2

You don't need to migrate existing BPs from ODF to ODF2 if you haven't faced any ODF limitations impacting BP quality. The Product supports the execution of BPs created on both versions of ODF.

OCR

High-level description

ODF 2

Major technical concerns of AI Agent delivery

Orchestrate AI Agent

The instruction describes running, stopping, and scheduling Business Processes based on the ODF 2 example project.

Orchestration workflow

The Orchestration section guides you through the steps to deliver and orchestrate automations, including the involvement of a human worker in the loop. The figure below illustrates the actions available for the purpose in the Control Tower (CT) and Workspace (WS) user interfaces.

Package AI Agent Asset Bundle

The article describes an AI Agent Asset Bundle. For details on the structure of an AI Agent Variation Asset Bundle, refer to Package assets into AI Agent Variation Asset Bundle.

Package assets into AI Agent Asset Bundle

The article describes an AI Agent Asset Bundle. For details on the structure of an AI Agent Variation Asset Bundle, refer to Package assets into AI Agent Variation Asset Bundle.

Predefined task types

There are some useful prepackaged task types not associated with any APIs. You can use them in the standard cross-process flow.

Process transactions with REST connector

The REST (HTTP) connector is an external connector that listens to incoming HTTP requests and sends records to Control Tower (CT). Optionally, for sync requests only, it can also return transaction results as an HTTP response.

Review example project

The ODF 2 example project is created to demonstrate key features of the framework. It contains four simple Business Processes that operate on a mock data model. While functional, these processes do not perform anything practically useful.

Software development life cycle

Software development life cycle (SDLC) is a process for planning, creating, testing, and deploying an information system. The instruction focuses on a recommended SDLC approach for the Work.AI automation solution implementation.

Split and join Transactions

ODF 2 allows splitting a Transaction into multiple sub-transactions and joining them back. This is usually done to process some data from the original Transaction in parallel.

Start Business Process by internal event

If you have several Business Processes (BP) where one BP produces data for another, you can apply the event-based communication mechanism and configure the data transfer between them. You can set a sub-process to start from another BP based on a specific event or set transaction processing to be launched from another transaction in a different BP using no-code sub-process steps.

Use OCR Bridge step

The article is an example of the OCR Bridge step usage in the scope of the ODF 2 framework. The Bot Tasks used in the example are a part of Processing Business Process from the example project.

Use pre-packaged components

The Open Development Framework provides several prepackaged components that are ready for drag-n-drop usage.

View all Business Processes

To access the list of Business Processes (BP), log in to Control Tower and go to Business Processes > View All.

Waiting for Transactions

A commonly encountered task in ODF 2 is waiting for the completion of all transactions in a given Business Process. There is no out-of-the-box solution that fits all use cases. For example, a Monitor Task often serves as the source of transactions, making it impossible to know when new ones appear. However, once all requirements are known, such a feature is quite easy to implement.

Work with Transactions

To illustrate how user Transactions are created and processed, let's simulate a simple scenario for a Business Process (BP) consisting of two Bot Tasks: