This is a glossary of terms for Blue Prism Cloud.

Generic terms



Application Object

The name given to objects created in Blue Prism Cloud which define a set of configuration rules that specify how a digital worker or workforce should interact with an application by replicating human interactions.

Application Server

A component that manages database connections and removes the need to configure direct connections between the various Blue Prism components and the database. When implemented, all Blue Prism components (interactive clients and runtime resources) connect to the Blue Prism Server service.

Component Library

The name given to the repository containing common and reusable automation utilities and procedures which can be used as part of an automation workflow.

Credential Store

A secure repository for retention or encrypted access credentials which may be required by a digital worker when executing a process.

Digital Worker

The name given to the resource within the platform which executes the defined automated processes it receives, interacting with the various local and remote applications, systems, tools, and devices required to complete the process. The digital worker is a Windows runtime component, it is the execution layer and emulates the activities of a human. It takes a process, an item, and the necessary credentials and follows the procedural steps to complete the defined task(s).


SS&C | Blue Prism® Hub is a web-based technology platform that provides access to plugins, including SS&C | Blue Prism® Interact and SS&C | Blue Prism® Automation Lifecycle Management.

IADA® (Intelligent Automated Digital Assistant)

An API which is used by Blue Prism Cloud components to receive and orchestrate work items.


A shared instance of IADA® which allows access to an evolving range of proprietary and third‑party cognitive services which can be called as actions from within a workflow and configured by any automation designer or business user.

Intelligent Automation

Intelligent Automation, also referred to as Intelligent Process Automation (IPA) is a term used to reference a combination of robotic process automation and artificial intelligence to provide a more capable digital workforce.

IADA iOCR (Intelligent OCR)

An extension of IADA OCR which uses Machine Learning to manage variation of extracted data into a form which recognizes, structures, and interprets that data, and learns from both historic activity (heuristics) and human input (governed learning) to improve over time.


A sub-component of the platform which manages the extraction and translation of information from document images into machine-usable data using optical character and image recognition approaches.


An intuitive web-based interface that allows internal or external users to interact with digital workforces, triggering execution of automated processes by creating submissions, providing input by completing information or approvals, and/or observing outputs.

NLP (Natural Language Processing)

The industry term which refers to the ability to understand, interpret, and process human language as it is spoken or written, as utilized by iOCR and IADA.ai. Sub-components of the definition include Natural Language Understanding, Natural Language Analysis and Natural Language Generation.


The name given to the digital workforce technology, provided as a subscription-based Platform-as-a-Service (PaaS) onto which customers or partners build business process workflows to automate and digitize work.


The name given to an object-oriented workflow configuration which links decision logic, application objects and other processes to create an automated and digitized work process.


Robotic Processing Automation (RPA) is the process of a digital worker mimicking a human’s actions to complete a rules-based task.


Recovery Point Objective (RPO) refers to the amount of data at risk. It is the time between data protection events and reflects the amount of data that potentially could be lost during a disaster recovery.


Recovery Time Objective (RTO) refers to the amount of time taken to recover the environment in the event of a disaster occurring.

Surface Automation

The technique used by an application object which connects to an application presented through Citrix, RDP, or another thin-client technology by employing image recognition.

Component-specific terms

Blue Prism



Action An Action stage allows a business object to be used in a process. It is similar to a Page Reference in that it takes the flow of the process down to another page, but instead of being in the same diagram it is a page within a business object.

Blocks are used for a variety of purposes, such as:

  • Grouping variables, for example, inputs and output parameters for easier readability
  • Exception handling, to facilitate handling exceptions thrown by different stages
  • To avoid infinite loops raised due to exception handling
Business Exception A business exception is a “planned” exception. This is an expected break in a business process because of potentially missing or incorrectly formatted data. These exceptions can be planned for in the automation and may be recoverable.
Business Object

A business object is an object that models the applications that the digital worker interacts with. It normally has multiple pages to simulate the functions of an application such as:

  • Opening and closing an application
  • Writing into fields
  • Reading messages on screen
  • Clicking on buttons and menu items.
Component A component is a mid-layer object that allows you to group common actions from one or more objects together to create a reusable and flexible module that can be embedded in your process workflow, but can also be used in other workflows. Creating these bite-size chunks will improve delivery and follows a holistic deployment approach.
Data Item

Data Items are containers for variables. They are where values are stored that can be used with automations. They can support different types, including:

  • Binary
  • Date
  • DateTime
  • Flag
  • Image
  • Number
  • Password
  • Text
  • Time
  • TimeSpan

For more information, see Data Types in the Blue Prism documentation.

Environment Variable

An environment variable is a dynamic-named value that can affect the behavior of running processes on a computer. They are part of the Environment in which an automation runs. Once an environment variable has been created it is available for use in Object or Process Studio. Environment variables are used to keep the value of that variable dynamic and can be referenced whenever required.

Page A page is a mechanism for splitting up a complex processes. Pages allow the process to be defined in smaller, less complex sections which can be tested in isolation. A Page Reference is used to join the pages and its contents together.


A process is intended to obey instructions performing a repetitive task. Those instructions could be, for example, extracting data from a spreadsheet. Alternatively, a process might be designed to launch an application and check a diary for available slots for patient appointments.

Queue Item

A queue item is a job that is in a work queue waiting to be processed.

Queue Item Key

The queue item key is a unique identifier of the queue item within the work queue.


Stages are items that can be used within an automation to simulate the interactions of a human performing a task.

For a complete list of the stages, see Stage types in the Blue Prism documentation.

System Exception

This is an “unplanned” exception typically caused by a failure of a server, service, network, or infrastructure resource. These may be recoverable if the event recovers in a predictable time and the automation has waited for the resource to become available. Otherwise these are unrecoverable exceptions.

Work Queue

A work queue is an internal configurable list that enables a process to manage its workload. A process can use different work queues and a work queue can be shared by multiple processes if required.





Self-contained features that can be individually installed to provide information about your digital workforce.


Roles control access to Hub and the plugins. They also define the level of access, for example, a Hub administrator or a Hub user.

In addition, there are some automatically generated roles based on the plugins that have been installed. These roles cannot be deleted, but users can be added to and removed from them.


A small-scale version of plugins that is used on the Hub Dashboard.

IADA NLU (Natural Language Understanding)




The application is a container for a specific process or group of processes. The NLU application is what a digital worker connects to, to have a data item processed in order to understand unstructured language. The input (data item) is referred to as an utterance. Intents and entities are returned to the digital worker or to a queue dependent on the process configuration.


There are four types of custom entity types within an NLU Application; Simple, List, Hierarchical and Composite.

Custom: Composite

A composite entity is made up of other entities that form parts of a whole. A composite entity can consist of up to 20 child entities. These count towards the maximum number of entities you may use.

Custom: Hierarchical

A hierarchical entity defines a category and its members. It is made up of child entities that form the members of the category. A hierarchical entity can consist of up to ten child entities. These count towards the maximum number of entities you may use.

Custom: List

A list entity represents a fixed set of synonyms or related words in your process. Each list entity may have one or more synonyms. They are not machine-learned and are best used for a known set of variations on ways to represent the same concept. List entities do not have to be Annabelle in utterances or trained by the system. A list entity is an explicitly specified list of values. Unlike other entity types, a NLU Application does not discover additional values for list entities during training. Therefore, each list entity forms a closed set. Your NLU Application may use up to 50 list entities, and they do not count toward the maximum number of list entities you may use, which is 30. Each list can contain up to 20,000 items.

Custom: Simple

A simple entity is a generic entity that describes a single concept. These count towards the maximum number of entities you may use in your NLU Application. An example would be company, travel agency, and so on. “Book my travel through Gobibo travel agency.” or “Please book my travel with MakeMyTrip agency.” or “Arrange my travel with Yatra travel agency.” or finally “Prefer to book my travel through ClearTrip.”.


If intents can be described are verbs, then entities are nouns. Entities are parameters required to process the user request and may also be data items in their own right to be used within an automation. In the utterance, “I would like to change my address to my new residence in Swanley” “Swanley” is an entity of type location. By recognizing the entities that are mentioned in the user’s input, the NLU Application helps you choose the specific actions to be executed to fulfil an intent. A maximum of 30 entities is allowed in a NLU Application. Entity Types fall into two categories, Prebuilt and Custom.


You can add features to your NLU Application to improve its performance. Features help a NLU Application recognize both intents and entities by providing hints that certain words and phrases are part of a category or follow a pattern. When your NLU Application has difficulty identifying an entity, adding a feature and re-training can often help improve the detection of related intents and entities.


Intents are similar to verbs in a sentence. An intent represents actions the user wants to perform, commonly linked to a process (automation) on a 1-2-1 basis. It is a purpose or goal expressed in a user’s input, such as booking a meeting, making a council tax payment, or changing address. You can define a set of named intents that correspond to actions users want to perform in your Application. A Local Council NLU Application may define an intent named “Balance Check” which NLU processes from the utterance “I would like to understand the remaining amount on my account”. Another way of asking for the same intent may be “I want to check my account balance”, both utterances relate to the same intent. A maximum of 80 intents is allowed in a NLU Application.


These are built-in types that represent common concepts like dates, time, and geography. These do not count towards the maximum number of entities you may use in your NLU Application.


Training is the process of teaching your NLU Application by example to improve its language understanding. If you make updates by adding, editing, or deleting entities, intents, or utterances to your Application, you need to train your Application before testing and publishing. When you train a NLU Application, NLU generalizes from the examples you have labeled and learns to recognize the relevant intents and entities in the future, which improves its classification accuracy.


An utterance is a textual input from the user or digital worker that the NLU Application needs to interpret. It may be a sentence, like “I want to change my address” or a fragment of a sentence, like “Address Change”. Utterances are not always well-formed and there can be many utterance variations for a particular intent. The maximum length of an utterance is 500 characters. In the case of large utterances such as emails, the message may need to be processed or ‘trimmed’ before being sent to the NLU Application.





The level of confidence the technology has that the characters have been identified correctly.

Document Definition Template

Used to define a structure identifying specific fields or areas of text to extract information from.


The process to produce the output once extracted and verified.


The reading of information from the images identified using the Document Definition Template.

FlexiLayout Studio

Used to identify/create the specific areas or regions within a scanned document requiring capture during the recognition process.

Hot Folder

Location where the scanned images are sent prior to recognition.


The process of loading images from the Hot Folder.

Project Setup Station

Used to establish the profile and configuration for the specific project.


Used to control the overall process.


The process used to verify items that did not meet the 100% confidence level.

Verification Station

Used to verify documents or correct verification errors after they have been processed.




Cross-Queue Search

In traditional RPA deployments, work is aligned to a queue and work is selected on a First In First Out (FIFO) basis. Cross-queue search allows all queues to be searched in parallel.

GNPI (Get Next Prioritised Item)

A function available within IADA to allow a digital worker to select an item based on its importance. This function allows for cross-queue searching.

SLA and Priority Management

The term given to selecting work based on its importance. Each item (a task within one of the various queues of work) is tagged with a priority value and a SLA.





A holding area for a request that has been partially completed.


Elements that can be used within a form to capture information from the user.


An entity within Interact that holds a range of properties such as a fields, rules, roles, privilege checks, and association to a queue.


A collection of procedural steps which allow the digital workers to follow a business process, for example, a New Starter Process, allowing a digital worker to understand how a user is onboarded into the organization.


A container for items. Queues do not need to be associated to a process (new starter queue) but usually are.


Dictate how the fields behave depending on user interaction.


A value used to track the lifecycle of a submission.


The term given to a partially (Draft) or fully (Submitted) completed Interact form.