SAP Finance R2R Customization Optimizer
Run a deterministic, public demonstration of posting configuration, validation, substitution, enhancement and custom-development influence.
Run Finance R2R demoAI Architecture Lab
Interactive architecture reasoning grounded in enterprise controls.
The Lab combines permanent published content, deterministic evidence analysis, optional source-grounded narrative assistance and explicit human decision boundaries.
Ask the Architecture Lab
Use the single assistant at the bottom-right to access approved knowledge answers and optional source-grounded explanations without leaving the current page.
The assistant is available at the bottom-right of this page.
SAP AI Agent Demo Lab
Explore Finance R2R, ST22, ATC, batch-job and pre-deployment demonstrations without a live SAP connection.
Explore agent demos01Approved business question
02Scoped enterprise evidence
03Identity and policy check
04Deterministic analysis
05Model-assisted explanation
06Confidence and trace
07Human decision
08Audit and replay
Operating principles
Open research agendaDeterministic evidence before model assistance.
Evidence before recommendation
Facts, unknowns and source boundaries remain visible before any advisory direction.
SAP remains authoritative
The public Lab cannot connect to SAP, execute transactions or replace target-system validation.
Risk differs from confidence
Potential impact and evidence reliability are calculated and presented separately.
Human approval remains mandatory
AI may explain or organize evidence, but accountable professionals make architecture and implementation decisions.
Research tracks
Open research agendaArchitecture positions under active examination.
Governed SAP AI agents
Use deterministic evidence collection first, LLM reasoning second, and explicit human approval for consequential actions. Open theme
Agent execution traceability
Expose stage, evidence source, tool call, policy decision, latency and failure state without leaking secrets. Open theme
Prompt drift and traceability
Version prompts, policies, tools and model context together and link them to execution evidence. Open theme
Performance architecture and thin loading
Classify capabilities by P1/P2/P3 criticality, load only when needed, measure every route and make operations switches explicit. Open theme
MCP and ABAP Cloud wrappers
Use read-only, scoped tools with clear schemas, audit and connection health; avoid embedding credentials in agents. Open theme
Responsible autonomy
Start read-only, add controlled actions only with policy, approval, rollback and audit. Open theme
LLM orchestration, RAG and vector databases
Use deterministic public or enterprise evidence first; add retrieval, vector search and model orchestration only behind explicit security, quality, freshness and fallback controls. Open theme
Telemetry beyond LLM calls
Measure user-perceived loading, rendering, APIs, backend work, database time, dependencies, policy decisions, retries, failures and recovery without collecting restricted content. Open theme
Human-in-the-loop operating controls
Define human checkpoints by risk, action scope, evidence quality and reversibility rather than placing approval at the end of every workflow. Open theme
Enterprise agent control planes
Use a federated control-plane model for identity, policy, catalogue, trace, release, telemetry and human accountability while preserving domain-specific execution. Open theme