← All answersSources checked: 2026-06-23
Process intelligence vs process mining
A direct buyer answer: process mining analyzes event logs, while process intelligence adds models, owners, governance, action, and live context.
Direct answer
Process mining reconstructs how work actually runs from event data. Process intelligence keeps that evidence connected to process models, ownership, KPIs, external signals, governed actions, and audit trails.
Best fit
- Use Geist when teams need the model, the data, and the next action in one place.
- Use classic process mining when the main question is discovery, variants, conformance, or cycle time inside existing event logs.
Pressure points
- Event logs show reality; BPMN and org context explain what should change.
- Live process intelligence is stronger when AI agents need boundaries, approvals, and evidence.
- Messy inputs matter: workshops, PDFs, screenshots, APIs, logs, and external signals rarely arrive as clean event logs.
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FAQ
Frequently asked questions
01Is process intelligence the same as process mining?
Process mining is usually one important engine inside process intelligence. The wider process-intelligence layer also handles models, owners, controls, recommendations, and action tracking.
02When is process mining enough?
When the task is limited to event-log discovery, conformance, variants, or bottleneck analysis. It is usually enough for a focused diagnostic project.
03Where does Geist fit?
Geist is built for teams that want observed process data, editable BPMN, org ownership, AI suggestions, and governed execution in one operating surface.
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