JD Edwards EnterpriseOne Private AI Layer Blueprint Generator
Answer a few questions about your JD Edwards EnterpriseOne estate and this generator writes a complete architecture plan for a private AI layer: components, security controls, a three-phase rollout and the questions your IT team still has to answer. Everything is editable, and you can export it as a document.
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JD Edwards EnterpriseOne Private AI Layer Blueprint Generator
Context
Company: Lakeshore Industrial Pumps System: JD Edwards EnterpriseOne 9.2 (Tools 9.2.7 or later) on Oracle Database Scale: 420 named users; 3 business units groups, 2 plants AI layer hosting: On-prem server; GPU position: None yet Target go-live: Q2 2027
Goal: add a private AI assistant on the existing system without moving data off-site. The assistant answers questions from live system data and documents, shows the data behind each answer, respects existing user permissions, and proposes changes for human approval.
Use cases in scope
Open sales and purchase order status, item availability and ledger, work order status, customer and supplier lookups, search of media object attachments
Data that must stay on site
Customer pricing and costing, engineering documents, export-controlled drawings
All model serving, indexing and logging for these data sets run inside the On-prem server boundary. No data is sent to an external model service.
Components
| Component | Design for JD Edwards EnterpriseOne | Notes |
|---|---|---|
| Data access path | AIS Server data service (user token) for lookups; read-only replica for large scans; Orchestrator for approved actions | Reads are read-only; no direct writes to production tables |
| Retrieval index | Media object attachments and shared-drive documents, with business unit and document type as the label | Embedding model runs locally; ACL stored with every chunk |
| Model serving | Open-weight model served with vLLM or Ollama on None yet | Size the model to the GPU; add a second node for availability |
| Tool server | Named tools for stock, orders, work orders and suppliers; Julian date and implied-decimal handling; Orchestrations for writes after approval | Named, parameterised tools; the model never writes free SQL |
| Identity and permissions | End-user AIS token so Security Workbench applies; replica tools restricted to data without unmappable row security | Acceptance test with a restricted user and a super user |
| Audit | Log of JDE user, tool, parameters, row counts and answer; review monthly with the JDE security administrator | Append-only; reviewed by IT and the system owner |
Security controls mapped to your inputs
| Control | Implementation | Driven by |
|---|---|---|
| Data residency | Model, index and logs inside the On-prem server boundary; no external API calls | Data that must not leave the site |
| Least privilege | Dedicated read-only account limited to listed objects | Use cases in scope |
| Permission mirroring | End-user AIS token so Security Workbench applies; replica tools restricted to data without unmappable row security | 420 named users and roles |
| Network isolation | Model host has no internet route for air-gapped; inbound only from the tool server | Hosting choice |
| Write-back control | Drafts only, then supported APIs after named human approval | Use cases in scope |
| Auditability | Log of JDE user, tool, parameters, row counts and answer; review monthly with the JDE security administrator | Internal audit and system owner |
Rollout plan
| Phase | Scope | Exit criteria | Typical duration |
|---|---|---|---|
| 1. Read-only questions | 5 to 10 named tools and document search for a pilot group | Answers match the system for a restricted and an unrestricted test user | 6 to 10 weeks |
| 2. Drafts | Assistant prepares documents or change requests as text for review | Reviewers accept drafts with low edit rate; audit log complete | 4 to 8 weeks |
| 3. Approved actions | Supported write path, each action approved by a named person | No action executes without approval; rollback procedure tested | 6 to 10 weeks |
Open questions for IT
1. Which Tools Release is in production, and is an AIS Server already deployed? 2. Which Security Workbench row and column rules affect the data in scope? 3. Is there a replica, and which database engine and replication method will feed it? 4. Which Orchestrations already exist and who owns them? 5. Where do media object files physically live?
Sign-off
Planning document, not a design guarantee. Confirm object names, API availability and licensing for your exact version and patch level with your vendor documentation and DBA. Compliance with any regulation remains the responsibility of your organisation.
Optional: have the blueprint reviewed
Send us your generated plan and we will point out gaps in data access, permissions and sizing for your JD Edwards EnterpriseOne environment.
Optional. The tool and every export work without this. No spam.
How to use it
Enter your version, database, hosting model, user count and sites. Describe the use cases in plain words and list the data that must never leave the site. The blueprint copies those inputs into a context section, a component table, a controls table that traces each control back to your answers, and a rollout table. Review the draft with the system owner and security officer, edit the open questions, and use the export as the starting point for a design review.
What the plan assumes for JD Edwards EnterpriseOne
The design reads from a safe access path, indexes documents in a local vector store, serves an open-weight model on your own hardware, and exposes only named tools. The system-specific path is: AIS Server data service (user token) for lookups; read-only replica for large scans; Orchestrator for approved actions. Permissions are mirrored from the system so that the assistant never shows data a user could not open directly.
- Read-only by default; no direct writes to production tables
- Model and index run inside your boundary, with an air-gapped option
- Every question and tool call is logged for audit
- Writes are drafted first and approved by a person
Reading the output
The context section is the summary a sponsor reads. The component table is for architects, and the controls table is for security and audit. The rollout table is deliberately conservative: phase 1 proves that answers are correct and permission-safe before any drafting or action. Durations are ranges that depend on data quality, licensing and how quickly access is granted.
Common mistakes
Teams often start with the model and leave identity and data access for later. Reverse that: decide how permissions are mirrored first, test with a restricted user, and only then tune the model. Also avoid pointing the assistant at production tables, giving it free-form SQL, or skipping the audit log.
Frequently Asked Questions
Does this plan require sending data to the cloud?
No. The design keeps the model, index and logs inside your boundary. Hosting can be an on-prem server, a private cloud you control or an air-gapped network. You can still add cloud services later if your policy allows.
Which GPU do we need?
It depends on the model size and the number of simultaneous users. A modest estate usually starts with one or two data-centre GPUs. Use the companion sizing calculator to estimate it from your own numbers.
Can the assistant change data in JD Edwards EnterpriseOne?
Only through supported interfaces and only after a named person approves the exact action. Phase 1 and 2 are read-only and drafting, so nothing writes to the system until you decide it should.
Is the output a finished design?
No. It is a structured starting point that your architects and DBAs should verify against your version, licensing and security policies before building.
Want a second pair of eyes on this plan? Netray builds private AI layers on JD Edwards EnterpriseOne and similar on-prem systems, and can review your draft with your team.
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