- Getting started
- Overview
- Installation
UI Agent user guide
Overview
UI Agent is UiPath®'s next-generation computer-using agents that bring intelligent automation directly to your desktop.
These agents understand natural language goals, such as "find the invoice from last month and download it", and autonomously navigate interfaces the way humans do, in order to achieve that goal, adapting to changes that would break traditional automations.
UiPath's objective is to integrate UI Agent with a proven automation platform, to deliver reliable, governed results.
UI Agent presents the following key features and value proposition:
Lowers Total Cost of Ownership (TCO) for automations
- Self-healing automation mechanisms that prevent workflows from completely breaking, even when the UI changes.
- More resilient than traditional selectors, adapting dynamically to different structures without requiring manual adjustments.
- Easier to target difficult elements.
- Deeply integrated into our RPA platform, enabling customers to seamlessly combine traditional RPA, API automation, and agentic capabilities, to leverage the unique advantages of each technology.
Lowers the development barrier
UI Agent enables the automation of complex interactions with ease, such as:
- Extracting data dynamically, e.g., retrieving items from a list based on semantic criteria.
- Selecting elements that change position dynamically based on content without needing adjustments.
- Corner cases that no longer require explicit development, provided they remain reasonably aligned with the appropriate path.
Enables previously infeasible tasks
- High-branching automation scenarios become viable, such as: automating repetitive entry of identical data across hundreds of different websites, that previously required custom development for each one.
Introduces new agentic and cognitive capabilities
UI Agent goes beyond traditional automation by enabling:
- Cognitive navigation – e.g. browsing a supplier websites to find products that match a specific set of semantic criteria.
- In-context decision-making – e.g. identifying the relevant GitHub repository from a candidate and composing customized outreach emails.
- Intelligent summarization – e.g. extracting insights from multiple sources, such as collecting peer feedback to identify employee strengths, and areas for improvement.
Enhances Computer Vision scenarios
- Complements and enhances Computer Vision automations, allowing for more robust and context-aware interactions.
Cross-platform Automation
- Support across Mac and Linux, ensuring broad applicability and ease of deployment.
