Enterprise Resource Planning
Financials, Procurement, Projects, Risk, Expenses and related ERP readiness intelligence. Quarterly release discovery supports transitions such as 26D → 27A → 27B → 27C → 27D when Oracle actually publishes them.
An autonomous Release Intelligence Engine for ERP, HCM, SCM, and EPM. It watches Oracle Cloud Readiness, detects newly published releases, builds source-traceable impact analysis, compares each release with the prior baseline, generates Excel + PDF artifacts, and preserves evidence for the next release cycle.
Financials, Procurement, Projects, Risk, Expenses and related ERP readiness intelligence. Quarterly release discovery supports transitions such as 26D → 27A → 27B → 27C → 27D when Oracle actually publishes them.
Workforce, Payroll, Recruiting, Talent, Compensation, Time and Labor, Benefits, Learning and shared-technology release intelligence.
Inventory, Procurement, Manufacturing, Planning, Maintenance, Order Management, PLM, logistics and common-component intelligence.
Monthly intelligence for Planning, FCCS, Tax Reporting, EDM, Data Integration, Calculation Manager, automation, APIs and platform changes. EPM keeps Oracle's native monthly versioning.
Every generated baseline is compared against the prior successful baseline using stable record identities and content hashes. The agent preserves Added, Updated and Unchanged findings and only calls something deprecated or retired when Oracle evidence supports it.
The agent always has a deterministic evidence-based analysis path. When an approved model credential is available, material features can receive a second AI interpretation pass without allowing the model to invent Oracle facts, patch IDs, maintenance packs or tenant status.
Sub Application, Release, Module, Feature, Update Type, Impact Analysis, Setup Effort, New Functionality, Steps to Enable, Tips and Reconsiderations, Key Resources, Change Type, and Maintenance Pack.
Release, Module, Known Issue, Description, Resolution, and Oracle Reference ID. Gated MOS evidence remains explicitly marked rather than fabricated.
Machine-readable JSON baselines preserve source evidence and record hashes so later releases can be compared consistently across 27A, 27B, 27C, 27D and beyond.