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AI Process Automation with ProcessMind

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AI Process Automation with ProcessMind

AI Features

Where AI Helps with Process Work

ProcessMind applies AI to three distinct tasks: creating and analyzing process models, assisting with data mapping, and sharing process context with external AI tools.

AI-Assisted Process Discovery

Use event log data to explore how your process runs.

  • Review process models and variants derived from event data.
  • Examine process flows alongside performance information.
  • Investigate bottlenecks and delays in the process.
  • Use the findings as a starting point for analysis, not as a substitute for your review.
Process discovery and charts
Process discovery and charts

AI-Generated BPMN

Describe a process in plain language and generate a BPMN model to review.

  • Start with a written description, such as how an invoice moves from receipt to approval and payment.
  • Generate a BPMN 2.0 model with tasks, gateways, and flows.
  • Refine the draft with drag-and-drop editing.
  • Use the model for documentation or as a starting point for process design.
  • Review the generated model before sharing or using it.
Generate your first model from a description
Generating a BPMN model from a description
Generating a BPMN model from a description
Editing a generated BPMN model
Editing a generated BPMN model

Bottleneck Analysis and Improvement Suggestions

Use AI to interpret process performance and identify areas to investigate.

  • Review summaries and suggestions based on your process data.
  • Examine bottlenecks, rework loops, and delays.
  • Place summaries and report elements on the canvas beside the process they describe.
  • Treat recommendations as proposals for the process owner to assess, not automatic decisions.
  • Revisit findings after uploading new data or applying filters.
Process performance recommendations
Process performance recommendations
Data mapping recommendations
Data mapping recommendations
Generate a BPMN model from a process description
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AI for Process Management

AI can help you create process models, prepare data, and understand performance, all in one place. ProcessMind brings these capabilities together with process discovery, modeling, and analysis.

AI DISCOVER

Use event log data to explore process flows, variants, and bottlenecks.

How it works

  • Upload event logs from your systems
  • Use AI to help identify case IDs, activities, and timestamps
  • Review the process model and its variants

What you get

A view of how your process runs in the data you provide.

AI GENERATE

Describe a process in plain language to generate a BPMN model you can review and edit.

How it works

  • Enter a process description
  • Generate BPMN with tasks, gateways, and flows
  • Review and edit the model with drag-and-drop
  • Ask the built-in AI assistant to add, change, or explain elements and expressions

What you get

A draft model you can refine for documentation or process design.

AI ANALYZE

Use AI-assisted analysis to understand bottlenecks, delays, and process performance.

How it works

  • Review process data for patterns and outliers
  • Examine bottlenecks and delays
  • Use the findings to decide where to investigate

What you get

Clearer evidence to guide your improvement work.

AI RECOMMEND

Review AI-generated summaries and suggestions based on your process data.

How it works

  • Review summaries and recommendations
  • Consider suggestions for addressing bottlenecks, rework, and delays
  • Revisit the analysis after uploading new data

What you get

Suggestions for your process owner to assess and approve.

AI SIMULATE

Use AI-suggested scenarios and parameters to support what-if analysis.

How it works

  • Review suggested simulation scenarios
  • Test possible changes in a simulation
  • Compare simulated results with actual performance

What you get

A way to explore possible changes before deciding what to do.

AI THROUGHOUT PROCESS WORK

Part of the platform

Use AI alongside process discovery, modeling, and analysis.

Start with your data

Upload process data to explore flows, variants, and performance.

Keep the process owner in control

AI proposes models and suggestions. You review them and decide what to adopt.

Control access to process knowledge

On the Enterprise plan, external AI access through MCP follows the security approach outlined in the MCP guide.

Generate a BPMN model from a process description
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Share Process Context with External AI Tools

On the Enterprise plan, ProcessMind can make process knowledge available to external AI tools through the MCP Server. The REST and Data API, available on every plan, also exposes process context. Connected tools can access relevant context, including process descriptions, documentation, roles, KPIs, and process mining insights. Access follows the security controls outlined in the MCP guide. Your process owner remains responsible for reviewing AI-generated responses and decisions.

MCP Server

Connect MCP-compatible AI tools to process context through the Model Context Protocol. Available on the Enterprise plan.

AI Context API

Use the REST and Data API, available on every plan, to provide AI tools with process context, documentation, and operational insights.

Choose Your AI Tools

Connect an AI assistant or build tools that use ProcessMind process knowledge.

Permission-Aware Access

External AI access follows the roles and permissions outlined in the MCP guide.

Process Knowledge

Make process descriptions, instructions, governance rules, and operational documentation available as context.

BPMN Model Context

Provide access to BPMN 2.0 models, including process flows, gateways, and decision logic.

Documentation Context

Use SOPs, work instructions, compliance policies, and process guides as context for AI tools.

Roles and Responsibilities

Include process ownership and responsibility information, including RACI models.

Process Mining Insights

Make process performance data, bottleneck analysis, variants, and improvement suggestions available as context.

Custom API Endpoints

Define API endpoints for specific process knowledge or analytics.

See our plans to find these features

Maturity Stage

Where AI Fits in Process Management

Use AI to support process modeling and analysis, then apply your process knowledge to decide what to improve.
Step 3 of 3
MATURITY LEVEL 1

Process Foundation

Model and document your processes to give teams clarity and a shared understanding.

Business Analyst Creates and maintains process documentation and BPMN models.
Process Owner Defines how work should be performed and ensures process standardization.
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MATURITY LEVEL 2

Process Architecture

Define and manage your process landscape to align operations with strategy and compliance.

Process Architect Designs the enterprise process landscape, governance structure, and ownership model.
Transformation Manager Aligns processes with strategy, compliance requirements, and business change initiatives.
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Next Step
MATURITY LEVEL 3

Process Intelligence

Use data and AI to understand performance, anticipate outcomes, and improve continuously.

Operational Excellence Manager Uses data to identify bottlenecks, monitor KPIs, and drive continuous improvement.
Process Mining Analyst Analyzes actual process execution, discovers inefficiencies, and validates improvements.
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Frequently asked questions

AI can assist with specific process management tasks. It can turn a written description into a BPMN model, suggest how to map source data to process concepts, and summarize patterns in process performance. On Enterprise, you can also make process context available to compatible external AI tools through MCP.

These capabilities support your work; they don't make decisions for you. Review generated models, validate mappings, and assess recommendations before acting on them.

Describe a process in plain language, then generate a BPMN 2.0 model to review. For example, describe how an invoice moves from receipt through approval to payment. The draft can include tasks, gateways, and flows.

Edit the model with drag-and-drop tools, or ask the built-in AI assistant to add, change, or explain elements and expressions. Use the result as a starting point for documentation or process design, then check it against how the work should happen.

For details on the generation workflow, see the AI process generation documentation.

AI can suggest how fields in your source data relate to process concepts. For example, when you prepare an event log, AI can help identify which columns represent the case ID, activity, and timestamp.

Check each suggestion against your source data before applying the mapping. The mapping determines how ProcessMind interprets the data in later analysis, so correct any mismatches before relying on the results. You can also review the guidance on AI data recommendations.

AI can summarize findings from process data and suggest areas to investigate. For example, if the analysis shows delays or repeated rework, AI can help explain those patterns and propose possible improvements.

Treat suggestions as proposals, not automatic decisions. Check the underlying data, consider operational context, and decide which changes make sense. Use process dashboards and KPIs to review performance alongside the analysis.

MCP, the Model Context Protocol, is available on the Enterprise plan and provides a way to make process context available to compatible external AI tools. Depending on the access provided, that context can include process descriptions, BPMN models, documentation, roles, KPIs, and process mining insights.

Access follows the security controls outlined in the MCP guide. External tools can use the context made available to them, but you remain responsible for reviewing AI-generated responses and decisions.

Read how MCP gives AI process context

AI-powered process management can help you turn process data into questions worth investigating. Use process mining to examine flows, bottlenecks, and variants. Review AI-generated summaries and suggestions, then apply your process knowledge to decide what to validate and whether to make a change.

ProcessMind also supports process modeling and simulation. Simulation lets you explore possible scenarios; it doesn't execute changes in your operations. For a broader view of the platform, see the process intelligence platform.

Check generated models against the process you intend to document. Validate data mappings against the source system. For analysis and recommendations, inspect the underlying evidence and account for context the data may not capture.

AI can help you prepare and interpret process information. You remain responsible for approving models and mappings and deciding whether to pursue improvement suggestions.

Try AI with a Process You Know

Describe a process from your own work and review the BPMN model AI generates. Start your free trial with no credit card required.

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