Process Intelligence Meets Execution Intelligence
The complete operational visibility required to operationalize enterprise AI.
The Missing Layer in Enterprise AI
More than 70% of enterprise leaders believe AI will significantly transform operations — yet fewer than 30% report achieving measurable productivity improvements from AI initiatives today.
Process mining platforms help organizations understand how processes move through enterprise systems. But the reality of enterprise operations includes a critical missing layer: the human execution layer.
Employees navigate multiple applications, perform manual data entry, interpret context, and make operational decisions that are never captured in system logs. Without understanding this layer, AI agent deployments fail and ROI is unmeasurable.
Blind AI Deployments
AI agents are built without understanding real operational workflows — targeting the wrong problems or missing the most impactful opportunities.
No Productivity Baseline
Organizations lack a clear baseline for how work is performed today, making it impossible to identify what should be automated.
Unmeasurable ROI
After deploying AI, enterprises have no way to measure whether agents actually improved productivity or reduced operational cost.
Two Intelligence Layers. One Solution.
The next generation of operational intelligence combines process intelligence with execution intelligence.
Process Intelligence
Celonis
Understanding how processes flow through enterprise systems using event logs and system data.
- ✓ Visualize complex operational processes
- ✓ Identify process variants and deviations
- ✓ Quantify inefficiencies and performance gaps
- ✓ Discover high-impact automation opportunities
- ✓ Automate improvements through action flows
Execution Intelligence
Pyze
Understanding how employees actually perform work inside enterprise applications — the telemetry that system logs miss.
- ✓ Baseline workforce productivity across applications
- ✓ Identify manual work, context switching, and inefficiencies
- ✓ Generate AI agent requirements from real behavior
- ✓ Measure productivity improvements after deployment
Better Together
Together, these intelligence layers create a unified operational data layer — the foundation required to operationalize enterprise AI with measurable impact.
Build AI agents based on real execution patterns, not theoretical process diagrams
Target the highest-impact automation opportunities with data-driven precision
Track productivity improvements and Agentic ROI in production
Quotable Quotes
“By combining Celonis' platform and Pyze's behavior telemetry, companies can achieve unprecedented insights into how employees actually get work done.”
Christopher Johnston
SVP - Head of Global Banking, Celonis
“Celonis gives us powerful visibility into standard processes. Pyze expands that intelligence into our custom workflows and homegrown systems.”
Mike van Bussel
Process Mining Consultant, Rabobank
The Operationalizing Enterprise AI Framework
Organizations that successfully deploy AI at scale follow a consistent four-phase approach.
Baseline Productivity
Analyze time spent across applications, context switching, manual data entry, process rework loops, and workflow variations across teams.
Identify Opportunities
Combine process-level bottlenecks with execution-level inefficiencies — swivel-chair activity, repetitive manual work, error-prone inputs.
Design AI Agents
Build automation based on real operational behavior — decision patterns, data fields accessed, action sequences, exceptions and edge cases.
Measure Agentic ROI
Track productivity improvements, reduced manual effort, decreased handling time, and process friction in production.
Unified Architecture
Enterprise Applications
Pega, Salesforce, SAP, Guidewire, Veeva, SaaS, Any Web Application
Celonis Process Intelligence
Process Mining & Process Optimization
Pyze Execution Intelligence
User Behavior + Workflow Telemetry
AI Agents & Automation
Intelligent automation based on real execution data
Continuous Productivity Optimization
Measurable Agentic ROI
Proven Results
Organizations deploying process intelligence with execution intelligence achieve measurable outcomes.
Workforce productivity improvement within weeks
Hours saved annually across financial crime operations
Operational savings identified in retail banking
Faster identification of automation opportunities
Customer Spotlight
Rabobank
One of the world's largest cooperative banks, Rabobank has adopted Pyze to enhance operational visibility across complex financial crime processes. By combining process intelligence with execution intelligence, Rabobank is able to understand how analysts perform work across systems and identify opportunities for automation and productivity improvement.
Results in 8–10 Weeks
A structured deployment model designed for speed and measurable impact.
Discovery & Configuration
Define scope, configure data capture rules, deploy to target applications
Data Collection & Validation
Capture execution data, validate accuracy, build initial analytics models
Analysis & Insight Generation
Generate productivity baselines, identify optimization opportunities, build dashboards
Executive Readout & Roadmap
Present findings, quantify savings opportunities, define automation roadmap
Ready to Operationalize Enterprise AI?
See how combining process intelligence with execution intelligence creates the foundation for measurable Agentic ROI.