AI and Intelligent Automation
Average increase in client revenue via AI optimization
Operational efficiency gains via intelligent automation
ESG reporting time reduction through our ESGAI platform
Perfect delivery track record across all AI projects
Intelligent Process Automation for SAP®
AI-driven automation of SAP business processes using inbuilt SAP automation.SAP® Business AI – Implementation & Enablement
Activate, build, integrate & deploy SAP Business AI solutions using SAP AI foundation on SAP BTP.Enterprise Business AI via LEO Platform
Build, integrate & deploy SAP Business AI solutions and Agentic AI using open‑standards‑based LEO platform.
Core capabilities and scope
- Automation of SAP processes across Finance, Supply Chain, HR, Manufacturing, IT, and Operations.
- AI-assisted automation decisioning embedded into SAP workflows and transactions.
- Integration of SAP with non-SAP enterprise systems (3rd party business applications, data platforms, collaboration tools).
- Replacement of manual, routine, or error-prone SAP operations with intelligent automation.
Business value
- Faster, more reliable SAP operations with reduced manual dependency.
- Tangible efficiency gains and cost savings.
- Automation aligned to real SAP process constraints — not generic RPA.
Core capabilities and scope
- Implementation using SAP BTP, SAP Joule, embedded AI, AI foundation viz. SAP AI services, AI lifecycle management and SAP Business data and context.
- AI use cases embedded directly into SAP transactions, workflows, and reports.
- PoC to production enablement with SAP-grade security, governance, and compliance.
- Integration with SAP S/4HANA, SuccessFactors, Ariba, IBP, and other SAP and non-SAP system.
Business value
- Fully SAP-aligned AI solutions with native integration and supportability.
- Faster adoption for SAP-standard enterprises.
- Enterprise-grade governance and long-term scalability within SAP’s ecosystem.
Core capabilities and scope
- Implementation of enterprise AI use cases using the LEO platform, including MCP server & client, AI agents, LLM orchestration, and machine-learning models.
- Build AI-powered insights, predictions, copilots, agentic workflows, intelligent automation, custom AI agents, RAG pipelines, custom ML models integrated into SAP transactions and UIs.
- Deep integration with SAP systems using APIs, OData, events, and SAP BTP connectivity.
- PoC-to-production enablement with enterprise-grade security, governance, and compliance.
- Use of enterprise-grade, open standards-based AI frameworks, tools and LLM models, selected based on performance, security, and governance needs.
Business value
- Greater architectural control through the use of open, standards-based and open-source AI components.
- Reduced long-term dependency on proprietary AI platforms while preserving SAP process integrity.
- Flexibility in model choice, deployment options, and lifecycle management.
- Faster experimentation and scaling with clear, governed paths to production.
- Enterprise-grade security, governance, and compliance across AI workloads.
Best fit for: Customers seeking Enterprise AI outcomes with reduced vendor lock-in, tighter cost control, faster ROI, deeper lifecycle management, and greater architectural flexibility.
01
Discovery of SAP® Business Processes for AI
Identify and prioritize high-value use cases across Finance, Supply Chain, HR, Operations, Audit and other business functions to maximize impact.
02
Preparation of Data & Environment
PreparationData & EnvironmentCleanse, validate, and structure SAP and non-SAP data and ensure readiness for AI adoption across SAP S/4HANA®, SAP Datasphere®, and SAP BTP®
03
Solution Design & Mapping to AI tools
Solution Design & Mapping to AI toolsBuild AI solutions that are aligned with business needs, current AI investments, budget, and timelines. Optimize the best-fit mix of SAP®-native (SAP AI Core, AI Launchpad), custom development and third-party AI capabilities.
04
Solution Implementation
ImplementationImplement, deploy, and scale AI solutions natively within your SAP® solution landscape.
05
Lifecycle Management
Lifecycle ManagementProvide continuous monitoring, performance optimization, and governance to ensure responsible AI adoption.
1
Align
Identify business priorities and pain points to ensure AI initiatives are closely aligned with organizational goals.
2
Assess
Discover opportunities for AI implementation through detailed analysis of current processes and data assets.
3
Act
Score, prioritize, and create quick win MVPs to demonstrate value and gain stakeholder buy-in.
4
Accelerate
Accelerate deployment of validated use cases across the organization for maximum impact.