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IBM Process Mining
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IBM Process Mining Features
What are the features of IBM Process Mining?
Process Management
- Process Library
- Collaboration
- Integrations
- Execution Management
Process Analysis
- Real-Time Process Analysis
- Process Notation
- Process Mapping
Automation
- RPA Integration
- Application Development
IBM Process Mining Categories on G2
Filter for Features
Process Management
Process Library | Provides users with a repository for process maps and documentation. This feature was mentioned in 116 IBM Process Mining reviews. | 96% (Based on 116 reviews) | |
Collaboration | As reported in 117 IBM Process Mining reviews. Allows for collaborative authoring of process documents. | 97% (Based on 117 reviews) | |
Integrations | As reported in 117 IBM Process Mining reviews. Provides various connectors and integrations to business applications and data sources. | 93% (Based on 117 reviews) | |
Execution Management | Based on 119 IBM Process Mining reviews. Gives users the ability to analyze processes, find bottlenecks and identify the gaps between how things should be and how they really are. | 94% (Based on 119 reviews) |
Process Analysis
Real-Time Process Analysis | Based on 119 IBM Process Mining reviews. Allows users to conduct real-time process analysis, as opposed to just historical analysis. | 96% (Based on 119 reviews) | |
Process Notation | Gives process notation capabilities. 118 reviewers of IBM Process Mining have provided feedback on this feature. | 94% (Based on 118 reviews) | |
Process Mapping | Based on 119 IBM Process Mining reviews. Provides tools for defining what a business entity does, who is responsible, to what standard a business process should be completed. | 96% (Based on 119 reviews) |
Automation
RPA Integration | As reported in 29 IBM Process Mining reviews. Integrates with RPA technology, either natively or via 3rd-party integrations. | 91% (Based on 29 reviews) | |
Application Development | Based on 118 IBM Process Mining reviews. Allow customers, partners and third-party developers to create applications on top of business processes. | 97% (Based on 118 reviews) |
Generative AI
AI Text Summarization | Condenses long documents or text into a brief summary. | Not enough data |
Agentic AI - Process Mining
Autonomous Task Execution | Capability to perform complex tasks without constant human input | Not enough data | |
Multi-step Planning | Ability to break down and plan multi-step processes | Not enough data | |
Cross-system Integration | Works across multiple software systems or databases | Not enough data | |
Adaptive Learning | Improves performance based on feedback and experience | Not enough data | |
Natural Language Interaction | Engages in human-like conversation for task delegation | Not enough data | |
Proactive Assistance | Anticipates needs and offers suggestions without prompting | Not enough data | |
Decision Making | Makes informed choices based on available data and objectives | Not enough data |
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