UiPath Agentic Automation Features

Gives users the ability to edit or write custom HTML, Javascript or CSS code.

Allows users to edit or write custom code with programming languages.

Provides tools for inserting brand logos, colors, quotes, and other proprietary content.

Provides base-level application templates to build atop and which users can customize for specifc users and actions.

Allows the creation ofpage sequences, forms, and libraries for users navigating the application.

Lets users add data from existing sources when creating the initial application or changing data sources.

Continuously updates data as users or external data sources are edited.

Encrypts or provides some form of firewall to prevent external parties from accessing sensitive data.

Releases the application for access on desktop or mobile devices.

Lets users build cross-platform applications or provide specific templates for different device types.

Provides ability to manage application and maintenance from build, throughout the release, and until it's deactivation.

Provides a visual editor to easily create automation models.

Offers the ability to record processes performed by humans to be recreated by bots.

Provides templates for workflows and processes for easier automation creation.

Allows developers to code custom automations.

Offers users the ability to reuse process automations and communicate with other team members around automation building.

Allows non-technical users to create bots in an easy, intuitive manner.

Equips administrators with the ability to schedule bot deployments in advance or on a consistent, regulated cadence.

Automates processes that supplement human action, often requiring human intervention and collaboration.

Automates processes completely without the need for human intervention.

Allows users to analyze the performance of bots via dashboards.

Insures data remains secure and compliant with industry standards.

Able to support large deployments.

Provides OCR capabilities in order to recognize text in documents and applications.

Allows for intelligent automation whereby the bot can imitate human behavior by learning from behavioral patterns.

Provides NLP capabilities in order to understand text in documents and applications.

Supports event or transaction based integrations that react to changes in real-time

Provides a web-based interface for designing, documenting, and testing APIs.

Allows for integration development through the visual development of integration logic flows with the help od a drag and drop user interface.

Facilitiates API development and integrations with prebuilt connectors, templates, and examples.

Provides the ability to create connectors from existing services and APIs in catalog.

Provides prebuilt, reusable connectors and workflows for all user integration requirements.

Enables multiple tenants (customers) to securely share physical computing resources.

Console for monitoring resource utilization, system health, ability to start and stop processes, etc.

Enables data routing on configuration basis and management of complex workflows through an orchestration engine.

Facilitates to and fro data map according to the data model between applications/web services.

Provides standard tools and functions to convert data values from the data format of a source system into the data format of a destination system.

Supports and oversees the management of API products across their full lifecycle

Employs data encryption both at rest and in transit.

Comply to key industry standards like SOC 2, ISO 27001, PCI DSS, HIPAA etc to protect and safeguard data.

Supports secure communication protocols like FTPS, SFTP etc

Assures the user that the system complies with industry regulations like GDPR.

Ensures that all data processed is encrypted for security.

Integrates data from disparate sources, without physical data movement

Provides one or more methods to securely transfer data from one location to another through a network

Provides integration to BigData sources such as Hadoop and other NoSQL sources (MongoDB, Cassandra and HBase)

Provides Integrations to EDI service providers.

Provides users with a repository for process maps and documentation.

Allows for collaborative authoring of process documents.

Provides various connectors and integrations to business applications and data sources.

Gives users the ability to analyze processes, find bottlenecks and identify the gaps between how things should be and how they really are.

Allows users to conduct real-time process analysis, as opposed to just historical analysis.

Gives process notation capabilities.

Provides tools for defining what a business entity does, who is responsible, to what standard a business process should be completed.

Integrates with RPA technology, either natively or via 3rd-party integrations.

Allow customers, partners and third-party developers to create applications on top of business processes.

Automatically assigns relevant followup tasks and notifies appropriate team members of status after testing.

Runs tests automatically and reliably according to the parameters and frequency defined.

Tests completely and thoroughly to minimize developer workload.

Supports deployment of integration apps both on-premisis and cloud environments/

Supports deployment of integration apps to a managed cloud environment

Provides developers with actionable insight after running tests.

Maintains a thorough history of test logs for future reference and analysis.

Grants developers granular control to define tests and test parameters.

Allows developers to automate a wide variety of test types according to need.

Condenses long documents or text into a brief summary.

Allows the user to process documents in various formats such as PDF, DOCX, and JPEG.

Gives user the ability to convert different types of documents into machine-readable text using Optical Character Recognition (OCR).

Enables the user to identify and extract specific entities like names, dates, and addresses from documents.

Gives user the ability to categorize sections of text within the document based on preset criteria.

Provides the user with the capability to validate the extracted data for accuracy.

Enables the user to process multiple documents in a single batch operation.

Gives user the ability to connect to automation technology, such as robotic process automation (RPA).

Enables users to search through the content of processed documents easily.

Allows the user to track changes and manage different versions of a document.

Gives user the ability to train custom machine learning models for specific data extraction tasks.

Provides the user with the ability to analyze the sentiment expressed in the textual content of the document.

Allows the system to understand the context of words and phrases for better data extraction and classification.

Provides the user with the ability to integrate the IDP system into other applications through APIs.

Supports configuration using natural language instructions.

Allows users to customize the tone of agent.

Enables definition of clear security guardrails for agent actions.

Provides support across web, mobile, messaging apps, and other channels.

Allows customization of agent branding, including visual appearance and conversational style.

Equips agents with proactive response capabilities based on predefined triggers.

Facilitates seamless escalation to human employees for complex issues.

Provides analytics and reporting on agent performance and interactions.

Offers agents the ability to maintain contextual awareness across interactions.

Ensures compliance with data privacy and governance requirements.

Automates workflows and actions based on agent responses.

Allows the use of APIs for advanced agent configuration.

Enables interoperability with multiple platforms for unified experiences.

Allows integration with CRM data to ground agent responses in business context.

Supports defining task order, dependencies, and conditional logic in workflows.

Provides a visual interface for managing workflows without code.

Offers pre-built connectors for widely used business applications and systems.

Provides API and webhook support for building and managing custom integrations.

Provides AI-driven insights or suggestions to improve workflow performance and efficiency.

Supports initiating workflows based on schedules, user actions, or system events.

Provides a low-code or no-code interface for creating and modifying workflows.

Allows reuse of workflow elements such as templates, forms, or logic blocks.

Offers detailed audit trails to monitor changes and user activity within workflows.

Provides tools to manage access permissions based on user roles.

Offers real-time dashboards to track progress and automation impact.

Provides metrics and insights into workflow performance and bottlenecks.

Capability to perform complex tasks without constant human input

Engages in human-like conversation for task delegation

Anticipates needs and offers suggestions without prompting

Improves performance based on feedback and experience

Engages in human-like conversation for task delegation

Anticipates needs and offers suggestions without prompting

Accurately interprets complex, multi-step natural language prompts to understand user intent.

Effectively builds the necessary backend workflows, processes, and database schemas from the prompt.

Generates a visually appealing, logical, and user-friendly interface based on the user's description.

Maintains context throughout a conversational building process, understanding follow-up commands and refinements.

The architecture of the generated application is sound and capable of scaling to meet business needs.

The generated application is functional and ready for use with minimal-to-no manual intervention.

Allows for easy modification and customization of the generated application's visual design and branding.

Provides robust and straightforward capabilities for connecting to external databases and third-party APIs.

Capability to perform complex tasks without constant human input

Ability to break down and plan multi-step processes

Works across multiple software systems or databases

Engages in human-like conversation for task delegation

Anticipates needs and offers suggestions without prompting

Makes informed choices based on available data and objectives

Capability to perform complex tasks without constant human input

Ability to break down and plan multi-step processes

Works across multiple software systems or databases

Improves performance based on feedback and experience

Engages in human-like conversation for task delegation

Anticipates needs and offers suggestions without prompting

Makes informed choices based on available data and objectives

Capability to perform complex tasks without constant human input

Ability to break down and plan multi-step processes

Works across multiple software systems or databases

Improves performance based on feedback and experience

Engages in human-like conversation for task delegation

Anticipates needs and offers suggestions without prompting

Makes informed choices based on available data and objectives

Lets teams configure execution order and dependencies among AI components, ensuring workflows run smoothly and logically.

Streamlines the management of multiple AI models and agents by bringing them together into cohesive, automated workflows for complex business tasks.

Connects with a wide array of AI model APIs and external services, regardless of provider, within a single orchestration platform.

Enables the construction of sophisticated, multi-step AI workflows that combine specialized models for end-to-end process automation.

Integrates seamlessly with enterprise platforms such as CRMs, databases, and business applications for unified data and process flow.

Supports the setup of live data pipelines that move information instantly between AI components and enterprise systems.

Offers comprehensive dashboards to visualize KPIs and performance metrics for all orchestrated AI workflows.

Generates in-depth reports on workflow performance, resource consumption, and the overall business impact of AI orchestration.

Tracks and displays resource usage across all AI components, enabling proactive performance tuning and troubleshooting.

Dynamically manages and allocates computational resources, including GPU clusters, to maximize efficiency based on current workflow needs.

Scales AI workloads up or down automatically, adapting to fluctuations in processing demands and user traffic.

Provides insights into data flow, processing times, and success rates for each individual AI component within a workflow.

Ensures all AI workflows adhere to relevant regulatory standards and industry requirements.

Empowers organizations to enforce governance policies and compliance controls across orchestrated AI operations.

Facilitates the setup of role-based permissions and approval workflows for sensitive AI operations and deployments.

Maintains comprehensive logs and audit trails of workflow executions to support compliance and troubleshooting efforts.

Applies robust security protocols and policies to protect sensitive AI deployments and data flows.

Capability to perform complex tasks without constant human input

Ability to break down and plan multi-step processes

Works across multiple software systems or databases

Improves performance based on feedback and experience

Engages in human-like conversation for task delegation

Anticipates needs and offers suggestions without prompting

Makes informed choices based on available data and objectives

Effectively creates tests by recording or analyzing user interface interactions.

Accurately translates plain-language descriptions into functional tests.

Provides AI-driven recommendations for improving test coverage.

Tests effectively self-heal to adapt to changes in the application.

Identifies application elements even after their properties change.

Reduces the time and effort required to maintain existing test suites via AI.

Provides insightful dashboards and reports for understanding test results and overall application quality.

AI accurately identifies unintended visual changes or bugs in the user interface.

Analysis clearly pinpoints the root cause of test failures.