Best-Practice Baseline Comparison
AI configuration agents compare current ERP settings against curated best-practice baselines built from vendor recommendations, industry standards, and aggregated implementation knowledge. The agent exports all configurable parameters, classifies them by module and risk level, and flags deviations with business impact assessments. For each deviation, the agent provides the recommended value, the rationale, and the potential consequence of the current misconfiguration.
In production deployments, baseline comparison typically identifies 200-500 actionable findings per ERP instance.
- Export all ERP configuration parameters programmatically through APIs or database queries for comprehensive audit coverage
- Compare against curated best-practice baselines organized by ERP module, version, and industry vertical
- Classify findings by severity: critical (data integrity risk), high (security/compliance), medium (performance), and low (cosmetic/preference)
- Generate remediation recommendations with step-by-step configuration change instructions and rollback procedures
- Track configuration drift over time by comparing periodic snapshots to detect unauthorized or unplanned parameter changes
Security Configuration Auditing
ERP security misconfigurations expose organizations to fraud, data breaches, and compliance violations. AI security agents audit user permissions, role definitions, segregation of duties (SoD), and system-level security settings. The agent identifies excessive permissions, SoD conflicts, inactive accounts with active privileges, and missing audit trail configurations.
Cross-referencing security settings with actual user activity reveals permissions that are granted but never used, enabling least-privilege optimization.
- Audit role-permission assignments identifying excessive access grants and segregation of duties (SoD) violations across ERP modules
- Detect dormant accounts with active privileges that represent unauthorized access risk vectors
- Validate system-level security settings: password policies, session timeouts, encryption configurations, and audit trail enablement
- Cross-reference granted permissions against actual user activity logs to identify over-provisioned access for least-privilege remediation
Performance Configuration Analysis
Many ERP performance problems stem from misconfigured parameters rather than infrastructure limitations. AI agents analyze performance-impacting configurations including batch sizes, caching settings, index configurations, and job scheduling parameters. The agent correlates configuration settings with actual performance metrics (query times, batch durations, user response times) to identify which parameters contribute most to performance degradation.
This targeted approach resolves performance issues faster than broad infrastructure upgrades.
- Identify performance-impacting configurations by correlating parameter values with actual system performance metrics and user response times
- Analyze batch job scheduling configurations detecting overlapping schedules, resource contention, and suboptimal execution windows
- Review database-level ERP settings including buffer cache sizes, query timeouts, and connection pool configurations against workload profiles
- Generate performance tuning recommendations ranked by expected improvement magnitude and implementation risk level
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AI Agent Security Review Checklist
A 30-point security review for AI agents that can call tools and write to business systems, covering identity, permissions, prompt injection, data handling, and audit.
Infor LN SoD: Reviewing Segregation of Duties in Roles and Authorizations
SoD in Infor LN means no single user can both create and approve the same financial or supply chain transaction. LN grants access through roles and session authorizations, so an SoD review starts by exporting every user, role and authorized session, then testing the combinations against a conflict matrix. An AI agent can do this across thousands of users in one pass and explain each conflict in plain language, but a compliance owner still has to decide which conflicts are accepted with compensating controls.
If you only need a standard SoD report on LN, Infor's own governance and compliance tooling may be enough; an agent adds most value when you need custom rules, plain-language explanations and drift tracking between audits.
- Typical conflict pairs to test: maintain suppliers and approve payments, enter purchase orders and receive goods, change item or price data and release sales orders
- Export users, roles and authorized sessions from LN, then flatten them into one user-to-capability table the agent can check against the rule set
- Flag users whose combined roles create a conflict even though each single role looks safe
- Compare against actual transaction history to separate conflicts that were exercised from those that are only theoretical
- Re-run on a schedule so new role assignments are checked before the next audit, not after
Frequently asked questions
How do you check segregation of duties (SoD) in Infor LN?
Export users, roles and the sessions each role can run, define the conflicting capability pairs your auditors care about, then test every user against them. An AI configuration agent automates the export and the matching, lists each conflict with the roles that cause it, and re-checks after every role change. Findings still need a human decision on remediation or compensating controls.
Audit your ERP configuration with AI precision. Contact Netray for automated configuration review.