OakPilot Playground
Try OakPilot in the browser.
Try three browser-based examples of agents and automated workflows working with operational data.
AI can do more than answer questions.
Investigate Decide Act
The scenarios and enterprise data are simulated. They show solution concepts, interaction patterns and architecture; they are not customer deployments.
Interactive demonstration
Maintenance Intelligence
Investigate a recurring equipment problem using simulated maintenance history, operational events and technical documentation.
Simulated environment · No live customer data
Simulated investigation
What would you like to investigate?
Interactive demonstration
Operations Exception Agent
Detect an operational anomaly, correlate equipment and production signals, and determine what operations should investigate next.
Simulated environment · Fictional operational data
Operational exception
Northline Industrial · Utility Area B
Energy consumption+18%versus expected baseline
Production output+2%near normal range
Compressed-air demand+31%above expected demand
Primary anomalous assetC-17elevated load at low production
All facilities, equipment, events and values in this demonstration are fictional.
Simulated investigation
What should operations investigate?
Behind the demonstration
From operational signals to a governed action.
Operational data contextUtility data · Production context · Equipment telemetry · Maintenance information
↓OakPilot intelligence layer↓Operational reasoning↓Recommended intervention↓Governed enterprise actionA production deployment could connect through authorized industrial data platforms, historians or telemetry systems, ERP and maintenance systems, APIs, databases and enterprise workflows.
SAP specialization
In an SAP environment, comparable implementations could integrate SAP BTP, SAP APIs, S/4HANA business context, maintenance processes and other authorized enterprise data sources where appropriate.
Interactive demonstration
Business Process Agent
Resolve an enterprise order exception by combining inventory, logistics and customer context, then prepare the actions required to keep the order on track.
Simulated enterprise data · No live customer systems
Fulfillment exception
Sales order SO-10482
- Customer
- Gulf Industrial Services
- Product
- HX-440 Seal Assembly
- Quantity ordered
- 24 units
- Requested delivery
- 14 September 2026
- Primary warehouse
- WH-A
- Available at WH-A
- 17 units
Northline Industrial, the customer, order and all enterprise records are fictional. No live enterprise action is performed.
Simulated process analysis
Can this order remain on track?
- Exception
- Context
- Options
- Recommendation
- Proposed action
- Human approval
Behind the demonstration
From business exception to governed execution.
Enterprise process contextSales order · Inventory · Inbound supply · Logistics · Customer and business rules
↓OakPilot intelligence layer↓Resolution decision↓Governed enterprise action↓ERP / workflow / customer processA real implementation could connect to authorized ERP, CRM, inventory, logistics, procurement and workflow systems through APIs and enterprise integration.
SAP specialization
In SAP environments, a comparable implementation could use relevant SAP S/4HANA business objects, SAP BTP, APIs, Integration Suite and governed business workflows where appropriate.
Behind the demonstration
What would connect in a real deployment?
User / operational event↓OakPilot intelligence layer↓
Enterprise contextMaintenance system · Business data · Technical documentation · Operational events
↓Recommendation / governed action↓Enterprise workflowThe Playground uses local simulated data. In a production implementation, the same interaction pattern could be connected to authorized enterprise APIs, databases, documents and workflows.
SAP environment?
A comparable implementation could use SAP BTP, SAP APIs, enterprise data and relevant SAP business processes as part of the architecture.