Sherpa Process Discovery neural network is the best solution for automated identification and description of routine business processes because it uses deep learning algorithms to analyze large amounts of data and identify patterns in the data. This allows it to accurately identify and describe routine business processes without the need for manual intervention.
Sherpa RPA Process Discovery
Describe business processes easily using machine learning
Additionally, Sherpa Process Discovery can be used to identify and describe processes that are not easily visible to the human eye, such as complex customer journeys or supply chain processes. Finally, it can be used to quickly identify and document processes that are constantly changing, such as those in the financial services industry.
Operating modes
High-level metrics and indicators of the routine and repeatability of business processes at all user workstations
Detailed description of business processes for robotization at selected workplaces users
Surface observation
- Launching applications, browsers
- Working with windows and sites
- Typical key combinations
In-Depth Research
Surface observation and also:
- Clipboard Analysis
- Analysis of actions with specific controls inside windows and sites: buttons, links, fields, tables, etc.
Natural language processing
(lemmatization, NLP, NER)
Intelligent Decision Support
(process mining, generation of Petri nets)
Clustering and classification
Sherpa Process Discovery is a neural network that will find suitable processes for robotization
Track any programs and websites
Sherpa Process Discovery can track any programs and websites by monitoring the system’s processes and network traffic. For example, it can track a web browser’s activity, or the processes of a program like Microsoft Word.
Computer vision
Sherpa Process Discovery uses computer vision to analyze screenshots of user interfaces and identify user actions. This eliminates the need for integration and access to system logs, as the user interface is the only source of data needed. For example, neural network can detect when a user clicks a button, scrolls a page, or types in a text field without needing to access system logs.
Fast results
Sherpa Process Discovery neural networks are able to quickly identify patterns in data due to their ability to learn from past observations. This allows them to quickly identify correlations and trends in data, which can be used to generate results after a few days of observation. For example, a Sherpa Process Discovery neural network could quickly identify a pattern in customer purchase data that could be used to predict future customer purchases.
Processes analysis
Sherpa Process Discovery neural network uses a combination of natural language processing and machine learning to analyze text-based process descriptions and reveal lists of repeating processes, their variations, and build their diagrams. For example, it can identify a process of «creating a customer account» and its variations such as «creating a new customer account» or «updating an existing customer account». It can then generate a diagram of the process, showing the steps and their relationships.
High security
Sherpa Process Discovery neural network works by analyzing the behavior of users and processes within the enterprise security loop. It uses machine learning algorithms to detect anomalies and suspicious activities, such as unusual file access or network traffic. By doing so, it can identify malicious activities and alert the security team to take appropriate action.
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