Enterprise Programs
01 · Configuration
Enterprise Product Configuration
Product configuration built around business rules, validation and traceable decisions.
Proposed extension stack
Enterprise LLM
Power Automate
SharePoint
Case scope: The enterprise process, systems and control foundation reflects hands-on delivery patterns. AI and agent components shown below are proposed design extensions.
Approved product rules
Rule validation
Exception review
Decision history
At a Glance
Business problem
Rules spread across spreadsheets, product documents and SAP exports lead to inconsistent configuration outcomes
My contribution
Requirements ownership · product rules · validation · UAT · release governance
Current environment
SAP exports · product rules · SharePoint
Business value
Product rules are checked consistently, exceptions are visible and approval decisions are recorded.
Proposed AI extension · AI / Agent / Human
AI
Makes sense of product rules, flags conflicting requirements and uses prior approved decisions as context for future checks.
Agent
Checks requests against approved rules, sends exceptions to the right owner and records approved decisions for future reference.
Human
Product owners approve ambiguous configurations. Overrides are allowed and every decision with its reason is captured.
Current workflow
01Stakeholder need
02Business rules
03Product catalog
04Output QA
What I owned
Rule classification
Process design
Validation criteria
Acceptance criteria
UAT
Release governance
AI use-case definition
AI output requirements
Exception workflow design
Human-control requirements
Proposed AI-enabled architecture
SAP export→
SharePoint→
Deterministic rules→
Enterprise LLM→
Agent routes→
Human approval→
Decision logged
Technical design
MVP scenarios
Scenario 1
Valid configuration. All rules satisfied, no conflicts detected.
Pass
Scenario 2
Hard rule violation. Product A with Option X is a prohibited combination.
Fail
Scenario 3
Ambiguous configuration. AI detects a likely conflict with Rule 27 at medium confidence and routes to the SME with supporting evidence.
Review
Controls and governance
AI does not override hard validation rules. Those remain authoritative.
Insufficient context triggers a review request, not a guess.
Human override is available at any step.
Every decision and override reason is logged for audit.
Implementation note
Azure OpenAI is the proposed LLM for interpreting ambiguous product-rule conflicts.