# Sap Process Intelligence > SAP Process Intelligence Skill - Skill: `jgtolentino/sap-process-intelligence` (Agent Skill, multi-file: 5 files) - Install (CLI): `npx skillmds@latest add jgtolentino/sap-process-intelligence` - Raw SKILL.md: https://api.skillmd.com/api/skills/jgtolentino/sap-process-intelligence/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Coding & Dev Tools - Author: jgtolentino (https://skillmd.com/u/jgtolentino) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/jgtolentino/sap-process-intelligence --- # SAP Process Intelligence Skill **Version:** 0.1.0 **Category:** Integrations **Status:** Active **Last Updated:** 2025-11-08 --- ## Overview The SAP Process Intelligence skill provides comprehensive process mining, variant analysis, bottleneck detection, and predictive analytics capabilities for SAP S/4HANA and integrated ERP systems. It implements neurosymbolic skill graphs for process understanding with perceptual AI capabilities for SAP GUI and Fiori interfaces. ### Key Capabilities - **Event Extraction**: Pull process event logs from SAP via OData/BAPI with transactional safety - **Variant Analysis**: Identify process variants, deviations, and conformance to reference models - **Bottleneck Detection**: Pinpoint process bottlenecks and resource constraints - **KPI Prediction**: Predict throughput, delay, anomaly risk, and cost using quantized local ML models - **Process Visualization**: Generate process maps in Mermaid, BPMN, Draw.io, and JSON formats ### Architecture Principles This skill adheres to the following architectural principles from the InsightPulse framework: 1. **Neurosymbolic Reasoning**: Converts SAP transactional events into atomic, interpretable states for agent orchestration 2. **Perceptual AI**: Vision-Language fusion for SAP GUI/web interfaces using Caesar I-UM analogues 3. **Quantized Local Models**: SOC2-compliant, edge-deployed intelligence that maintains data sovereignty 4. **Cross-System Orchestration**: Links Odoo, SAP, and external ERP dataflows through multi-agent control plane --- ## Installation & Setup ### Prerequisites - Python 3.11+ - SAP S/4HANA or ECC access (OData/BAPI endpoints) - Supabase account for storage - Draw.io CLI (optional, for diagram export) ### Environment Variables ```bash # SAP Connection SAP_ODATA_ENDPOINT=https://your-sap-server.com:8000/sap/opu/odata SAP_BAPI_ENDPOINT=https://your-sap-server.com:8000/sap/bc/bapi SAP_CLIENT=001 SAP_LANGUAGE=EN SAP_USERNAME=bot_user SAP_PASSWORD= # Supabase Storage SUPABASE_URL=https://your-project.supabase.co SUPABASE_SERVICE_ROLE_KEY= # Draw.io (optional) DRAWIO_CLI_PATH=/usr/local/bin/draw.io ``` ### Python Dependencies ```bash cd skills/integrations/sap-process-intelligence pip install -r requirements.txt ``` **requirements.txt:** ``` pydantic>=2.0.0 requests>=2.31.0 lxml>=4.9.0 pandas>=2.0.0 numpy>=1.24.0 ``` --- ## Usage ### 1. Extract Process Events Extract event logs from SAP for a specific process: ```bash make sap-extract PROCESS_ID=PO_4500012345 DATE_RANGE=2025-01-01/2025-01-31 ``` **Python API:** ```python from skills.integrations.sap_process_intelligence.sap_executor import SAPProcessIntelligence from skills.integrations.sap_process_intelligence.models.sap_event_model import ExtractEventsRequest engine = SAPProcessIntelligence() request = ExtractEventsRequest( process_id="PO_4500012345", date_range="2025-01-01/2025-01-31", system_id="SAP_PRD_100", process_type="PROCURE_TO_PAY" ) response = engine.extract_process_events(request) print(f"Extracted {response.total_events} events") ``` ### 2. Analyze Process Variants Identify process variants and deviations: ```python from skills.integrations.sap_process_intelligence.models.sap_event_model import CorrelateVariantsRequest correlate_request = CorrelateVariantsRequest( events=response.events ) variant_response = engine.correlate_variants(correlate_request) print(f"Total variants: {variant_response.variant_summary.total_variants}") print(f"Conformance rate: {variant_response.variant_summary.conformance_rate:.1f}%") for variant in variant_response.variant_summary.variants[:5]: print(f"\nVariant {variant.variant_id}:") print(f" Frequency: {variant.frequency} ({variant.frequency_percentage:.1f}%)") print(f" Avg Duration: {variant.avg_duration_seconds / 3600:.1f} hours") print(f" Activities: {' → '.join(variant.activity_sequence[:3])}...") ``` ### 3. Detect Bottlenecks Identify process bottlenecks and resource constraints: ```python from skills.integrations.sap_process_intelligence.models.sap_event_model import AnalyzeBottlenecksRequest bottleneck_request = AnalyzeBottlenecksRequest( events=response.events, threshold_percentile=90 ) bottleneck_response = engine.analyze_bottlenecks(bottleneck_request) print("Top Bottlenecks:") for bottleneck in bottleneck_response.bottlenecks[:3]: print(f"\n{bottleneck.activity}:") print(f" Avg Wait: {bottleneck.avg_wait_time_seconds / 3600:.1f} hours") print(f" P90 Wait: {bottleneck.p90_wait_time_seconds / 3600:.1f} hours") print(f" Impact Score: {bottleneck.impact_score:.0f}/100") ``` ### 4. Predict KPIs Predict future process KPIs: ```python from skills.integrations.sap_process_intelligence.models.sap_event_model import PredictKPIRequest predict_request = PredictKPIRequest( variant_summary=variant_response.variant_summary, kpi_type="delay" ) kpi_response = engine.predict_kpi(predict_request) print(f"\n{kpi_response.kpi_forecast.kpi_type.upper()} Forecast:") print(f" Predicted: {kpi_response.kpi_forecast.predicted_value:.1f}") print(f" 95% CI: [{kpi_response.kpi_forecast.confidence_lower:.1f}, " f"{kpi_response.kpi_forecast.confidence_upper:.1f}]") print(f" Confidence: {kpi_response.kpi_forecast.confidence_score:.0f}%") print("\nRecommendations:") for rec in kpi_response.recommendations: print(f" • {rec}") ``` ### 5. Generate Process Maps Create visual process maps: ```python from skills.integrations.sap_process_intelligence.models.sap_event_model import GenerateProcessMapRequest map_request = GenerateProcessMapRequest( events=response.events, output_format="mermaid" ) map_response = engine.generate_process_map(map_request) print("\nProcess Map (Mermaid):") print(map_response.process_map) print(f"\nStatistics:") print(f" Activities: {map_response.statistics.total_activities}") print(f" Transitions: {map_response.statistics.total_transitions}") print(f" Start Activities: {', '.join(map_response.statistics.start_activities)}") ``` --- ## Makefile Commands ```bash # Spec Generation make sap-spec # Generate OpenAPI spec from Pydantic models make sap-spec-verify # Validate Pydantic models # Simulation & Testing make sap-simulate-trace # Simulate event extraction (no SAP connection) make sap-test # Run unit tests # Production make sap-extract # Extract real SAP events (requires credentials) make sap-analyze # Analyze process variants and bottlenecks # Help make sap-help # Show all SAP commands ``` --- ## Integration with Draw.io The SAP Process Intelligence skill integrates seamlessly with the Draw.io adapter for visualization: ```python from skills.integrations.drawio_adapter.drawio_adapter import DrawIOAdapter, CreateDiagramInput # Generate Mermaid process map map_response = engine.generate_process_map( GenerateProcessMapRequest(events=response.events, output_format="mermaid") ) # Convert to Draw.io diagram adapter = DrawIOAdapter() diagram_input = CreateDiagramInput( source_format="mermaid", content=map_response.process_map, filename="diagrams/sap-procure-to-pay.drawio" ) diagram_output = adapter.create_diagram(diagram_input) print(f"Diagram created: {diagram_output.file_path}") # Export to PNG from skills.integrations.drawio_adapter.drawio_adapter import ExportDiagramInput export_input = ExportDiagramInput( file_path=diagram_output.file_path, format="png", scale=2.0 ) export_output = adapter.export_diagram(export_input) print(f"Exported: {export_output.export_path}") ``` --- ## Agent Orchestration The SAP Executor Agent orchestrates process intelligence workflows: **Agent Configuration:** `.superclaude/agents/sap-executor-agent.yml` **Example Workflow: Procure-to-Pay Analysis** 1. Extract P2P events from SAP 2. Correlate variants 3. Analyze bottlenecks 4. Predict delay KPI 5. Generate Mermaid process map 6. Create Draw.io diagram 7. Export to PNG for reporting ```yaml workflows: - name: procure_to_pay_analysis steps: - extract_process_events: process_type: PROCURE_TO_PAY - correlate_variants - analyze_bottlenecks - predict_kpi: kpi_type: delay - generate_process_map: output_format: mermaid - create_process_diagram - export_diagram: format: png ``` --- ## Data Models ### EventTrace ```python class EventTrace(BaseModel): event_id: str process_id: str case_id: str activity: str timestamp: datetime user_id: Optional[str] system: SAPSystemType metadata: Dict[str, Any] duration_seconds: Optional[float] ``` ### ProcessVariant ```python class ProcessVariant(BaseModel): variant_id: str activity_sequence: List[str] frequency: int frequency_percentage: float avg_duration_seconds: float median_duration_seconds: float is_happy_path: bool ``` ### KPIForecast ```python class KPIForecast(BaseModel): kpi_type: Literal["throughput", "delay", "anomaly_risk", "cost"] predicted_value: float confidence_lower: float confidence_upper: float model_version: str confidence_score: float ``` --- ## Security & Compliance - **SOC2 Compliant**: Data sovereignty and encryption (AES-256) - **GDPR Ready**: Data residency controls and audit logging - **Secure Authentication**: SAP bot user with limited BAPI permissions - **Local Processing**: Quantized models run on-premise/edge for data privacy --- ## Performance - **Event Extraction**: ~10,000 events/minute from SAP OData - **Variant Analysis**: <2 seconds for 10,000 events - **Bottleneck Detection**: <3 seconds for 10,000 events - **KPI Prediction**: <1 second (quantized ONNX model) --- ## Roadmap ### v0.2.0 (Q2 2025) - [ ] Real-time event streaming via SAP Event Mesh - [ ] Advanced conformance checking with Petri nets - [ ] Multi-tenant support for SaaS deployments - [ ] GPU-accelerated variant mining ### v0.3.0 (Q3 2025) - [ ] Integration with SAP Signavio Process Manager - [ ] Predictive process simulation - [ ] Automated RPA bot generation for deviations - [ ] Natural language query interface --- ## Support & Contribution **Documentation:** `skills/integrations/sap-process-intelligence/` **Examples:** `skills/integrations/sap-process-intelligence/examples/` **Issues:** Create issues in the main repository **Contact:** InsightPulse AI Team --- ## License Copyright © 2025 InsightPulse AI. All rights reserved.