Process intelligence uses data from business systems and employee activity to explain how a process runs and where it needs improvement. An accounts payable team might use it to find out why invoices take four days to approve: are employees checking prices, waiting for a manager, or correcting data entered earlier? Each cause calls for a different change.
The term grew out of process mining. Gartner now calls the market it once labeled process mining “Process Intelligence Platforms,” and vendors use the broader name because their products now combine event-log analysis with desktop observation, business context, simulation and automation. SAP Signavio, for example, cites the 2026 Gartner Magic Quadrant for Process Intelligence Platforms on its product page.
The data process intelligence uses
System logs show recorded transactions. Screen activity shows the work between them. Procedures and employee interviews help explain why people took those steps.
System event logs. ERP, CRM and ticketing systems record events such as “invoice received” or “PO approved” with a timestamp and a case or object identifier. Process mining reconstructs case paths from these records. Vendors ship extractors for the big systems: Celonis cites more than 100 prebuilt extractors for on-premises and cloud ERPs, CRMs and data warehouses, and SAP Signavio offers prebuilt connectors for SAP and non-SAP systems.
Desktop and browser activity. Task mining records what people do on screen: applications used, fields edited, copy and paste between systems, and time spent. It covers work that never reaches a system log, such as checking a spreadsheet or searching a supplier portal. Microsoft describes task mining as capturing the detailed steps of tasks people perform on their desktops.
Documents and expert input. Procedures, policies and interviews explain why a step exists, which a log or a recording rarely does. WIQ, for example, reconstructs each process from recordings, systems of record, documentation and answers from experts.
- CollectEvent logs, desktop activity, procedures and expert input
- ReconstructLink records to cases or objects and rebuild the paths they took
- ExplainSeparate waiting, active handling, rework and required controls
- ActChange a rule, retrain a team, automate a step or deploy an agent
- MeasureCompare the same case types before and after the change
Keep the underlying cases available so the process owner can check the analysis.
How it differs from related disciplines
| Discipline | Evidence | What it answers | Blind spot |
|---|---|---|---|
| Process mining | Event logs from systems of record | Where cases wait, loop, skip steps or deviate from the model | Work that no system records |
| Task mining | Desktop and browser interactions | What a person does inside a step, and how long it takes | Business context outside the observed screens; small samples |
| Process documentation | Written procedures and BPMN models | How work is supposed to run | Exceptions and drift since the document was written |
| Business intelligence | Aggregated metrics from data warehouses | How much, how many, how fast, by segment | The sequence of activities that produced the number |
| Process intelligence | Any of the above, linked to cases and business context | Why the process performs as it does, and what to change | The same blind spots as its inputs, plus causal claims the data cannot support |
Older process-mining models typically followed one case type at a time, such as one invoice. Object-centric process mining links related objects, so an analysis can follow an order, its deliveries and its invoices together. Celonis built its platform around this approach, which it describes as the Process Intelligence Graph and object-centric process mining.
Several platforms also let teams act on the findings. SAP Signavio can trigger notifications, workflows or bots and connect to SAP Build Process Automation or third-party RPA tools. Celonis offers Action Flows with integrations to more than 2,000 apps and systems. UiPath combines process and task mining with simulation and conformance monitoring next to its automation platform.
A worked example: slow invoice approvals
Suppose an ERP log shows that the median invoice takes four days from receipt to approval, and that 30% of invoices pass through a “price change” activity before approval. Process mining establishes where the time goes between recorded events and which variant is slow. It does not show what anyone was doing during those four days.
Recordings of the accounts payable team reveal two different causes. In the price-change cases, clerks open the purchase order, compare unit prices against a supplier price list kept in a spreadsheet, email the buyer, and wait. For a second slow group, nobody touches the invoice for three days because it sits in an approver’s queue.
For the price-change cases, an automated comparison could flag the mismatch before a clerk opens the invoice. For the untouched invoices, the team needs to change routing or staffing. It could reassign an invoice after a set wait, for example. Automating the price check alone would leave that three-day queue unchanged.
Before removing the price check, find out why the team performs it. If it catches overpayments, the new process still needs that control.
How process intelligence feeds AI agents
To build an agent for the invoice example, a team needs to specify which price list to use, how to match its entries to purchase orders and who should review a mismatch. Observing employees work through those cases helps fill in details that a written procedure may leave out.
Vendors use this process data in different ways:
- Celonis launched an MCP server built for process intelligence to give agents operational context, and its Orchestration Engine coordinates agents alongside people and systems.
- SAP Signavio lists a Process Data Modeling Agent, in beta, that writes SQL and sets up event collectors.
- Skan and Mimica build agents from observed processes. Mimica’s Maker generates agent code and tests it against real examples of the work; Skan builds agents from observed patterns, business rules and pretrained skills.
- WIQ generates blueprints of steps, tools, guardrails and escalation paths from observed work, existing documentation and team input, then deploys them as agents in WIQ or through Claude, Microsoft Copilot, OpenAI, Workato or another MCP-compatible platform.
After deployment, the same evidence provides the baseline. Compare the agent-assisted process with the original on completed cases, errors, human review time and cost, keeping cases that people still finish manually in the count.
Where to start
Start with a process the team already wants to improve. Check what its systems record before installing another tool. An ERP may show how long invoices wait for approval but omit the spreadsheet checks that occupy the accounts payable team.
Use event-log analysis to investigate the wait. Add task observation if you also need to understand the manual checks, with capture scope agreed before recording starts. Ask the process owner to verify the findings against actual cases before estimating savings or commissioning an agent.
Our process intelligence software comparison covers the different approaches. The task mining tools comparison focuses on recording and analyzing desktop work.
Common questions
Is process intelligence the same as process mining?
Process mining is the core technique: reconstructing process paths from event logs. Process intelligence is the broader category that adds other data sources, business context, simulation and tools for making changes. Most vendors that once sold process mining now sell under the process intelligence name.
Does process intelligence require event logs?
Event-log analysis does. A process intelligence project can also start from desktop observation and documents when the work runs through email, spreadsheets and portals that write no usable log.
Can process intelligence decide what to automate?
It can rank candidates by volume, effort and variation, and some products score automation readiness. A deployment decision still needs the business rules, access requirements, failure consequences and an estimate of review effort, which a process owner has to confirm.
How is process intelligence different from business intelligence?
Business intelligence reports outcomes such as volume, revenue or average cycle time. Process intelligence reconstructs the sequence of activities behind those outcomes, so it can show which path through the process produced a slow or expensive case.