Process Intelligence
We help organizations uncover how work really flows across teams, systems and decisions - exposing bottlenecks, rework and hidden inefficiencies before automation or transformation begins.
Process Mining reconstructs how processes actually run based on event data from enterprise systems. It helps uncover bottlenecks, variants, rework, compliance gaps, and the best opportunities for improvement or automation.
Event logs from ERP, CRM, ITSM, finance, logistics, and other operational systems.
Maps based on real execution paths, variants, waiting times, and handoffs.
Root-cause analysis, conformance checks, KPI monitoring, and identification of improvement opportunities.
Transform your business by leveraging Process Mining to gain a comprehensive, data-driven view of your operations.
See the full process flow across systems, teams, and handoffs instead of relying on assumptions or workshop documentation.
Model improvement scenarios, estimate their impact, and prioritize initiatives by expected return and operational effect.
Combine system event data with user-task visibility to uncover manual work, execution variants, and the best candidates for automation.
Turn insights into action by connecting process mining with RPA, workflow, and other automation tools.
Continuously monitor process KPIs and detect regressions or improvements in real time.
Embed insights into operations with governance, training and stakeholder alignment to secure benefits.
Expandable guide with practical examples: from process discovery and root-cause analysis to automation decisions.
Event data foundation
Logistics value chain view
Variant and deviation map
Root-cause drilldown
Controlled workflow action
Create an evidence-based baseline before redesign, optimization or automation decisions are made.
When employees interact with different systems and applications, they leave traces of activity in data called event logs.
Process mining uses this data to visualize the real process flow in the organization and reveal delays, variants, and hidden inefficiencies.
The process mining platform pulls this data from source systems through connectors and builds process maps, root-cause views, and automation opportunities.
Focus the analysis on the highest-value segment of the operation and compare multiple business perspectives without rebuilding the model.
Process mining supports all key logistics activities in the value chain, including core operations and critical back-office processes.
A common use case is outbound order management, which can be analyzed from multiple business perspectives.
After a one-time data connection, you can immediately switch between productivity, service level, and customer satisfaction views.
Quantify where process variants move away from the ideal flow and where leakage, returns or rework begin to build.
Start with revenue leakage in outbound logistics. Process mining explores process data and shows all existing variants.
From the happy path to unknown violations and deviations, every iteration is visualized and measured.
With full process transparency, teams can pinpoint which activities drive revenue loss and build more resilient process decisions under uncertainty.
Returns are one of the top inefficiencies in outbound logistics: they add cost and consume time without creating value.
Separate symptoms from source drivers so teams can act on the real causes of variation, delay and avoidable returns.
The total impact of returns can be measured automatically, and teams can deep-dive through process dimensions to find root causes.
Fast and automated root-cause detection is crucial for reducing returns and improving process quality.
Process mining helps separate returns caused by quality issues, short picks, price changes, or long execution times that drive cancellations.
Automation delivers value only when the process is already controlled; otherwise the same inefficiencies scale faster.
Not every inefficiency can be fully eliminated. Process mining supports a sequence: examine the process first, remove major deviations, and then automate.
Automation improves outcomes only when the process is already controlled. Otherwise it can scale the same errors.
If returns cannot be eliminated entirely, process-driven automated workflows still make them less costly and less disruptive for operations.
Most organizations believe they understand their processes. In reality, what’s documented in procedures often differs from what actually happens in systems and operations. Process Mining allows you to move from assumptions to facts.
At Rhenai, we use Process Mining to reconstruct real, end-to-end business processes directly from system data — revealing inefficiencies, compliance risks, and automation opportunities that remain invisible in traditional analyses.
We work with leading platforms to deliver a data-driven view of how processes truly run — and turn insights into measurable improvements.
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Leverages data mining and process intelligence to deliver actionable insights: performance analysis, bottleneck identification, and validation of improvements. It reconstructs real end-to-end flows across enterprise applications, captures desktop interactions, and maps extracted data into process models for discovery, monitoring, and comparison vs. simulated automation.
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Open DemoIntegrates with enterprise systems and third-party automation tools. RPA bot generation supports creation of scripts and bot frameworks aligned to your automation stack. Built-in accelerators can automate ETL activities to efficiently extract, transform, and load data from core systems.
Complements process mining by capturing user interaction data to expose manual work and its impact on end-to-end performance. Helps identify best candidates for automation, estimate cost/impact, and validate initiatives before rollout. Continuous monitoring, thresholds, and alerts support operational control and sustained process excellence.
Part of an ecosystem including Task Mining, Task Capture, and Automation Hub — enabling discovery, evaluation, monitoring and governance across the automation lifecycle. Near real-time insights help accelerate programs, prioritize initiatives, and improve delivery at scale.
A global leader in AI-powered process mining and process excellence. Supports discovery, simulation, root-cause analysis, and predictive analytics. Widely adopted in industries such as logistics, financial services, and manufacturing to drive continuous improvement across complex operations.
Use process mining to identify hidden inefficiencies and improvements