SAP PI/PO private AI layer blueprint generator
This generator turns a few facts about your SAP PI/PO landscape into a structured architecture plan for a private AI layer: data access path, reporting copy, retrieval index, model serving, tool server, identity and audit. Export it to PDF or Word and take it to your architecture and security review.
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SAP PI/PO Private AI Layer Blueprint Generator
Private AI Layer Architecture Plan: SAP PI/PO
Prepared for: Acme Precision Ltd System: SAP PO 7.5 (single-stack AEX) on Microsoft SQL Server Hosting: On-prem server Named users: 25 Sites: 1 integration hub, 4 plants Target go-live: 2027-03-31
Context and scope
Acme Precision Ltd runs SAP PO 7.5 (single-stack AEX) and wants an AI assistant that works on its own data without moving that data to an external service. The assistant is read-only first, answers with cited records, and writes back only through supported interfaces after human approval.
Main use cases: Interface catalogue Q and A, failed message triage, mapping explanations, change-impact questions, migration inventory
Data that must never leave the site: Message payloads with personal data, pricing, controlled technical data, channel credentials
Components
| Component | Design | Notes |
|---|---|---|
| Data access path | Exports of ESR and Integration Directory objects as XML; monitoring data through the documented monitoring functions of your support package; message log metadata | Payloads excluded by default; confirm the monitoring API set on your version |
| Reporting copy | Reporting store holding interface graph and message events (metadata and error text) for Acme Precision Ltd | Collector runs on a schedule with read-only monitoring access |
| Retrieval index | Interface graph, mapping descriptions, channel types, runbooks, incident tickets, adapter documentation | Rebuild after transports |
| Model serving | Open-weight model on vLLM or Ollama, Two to four data-centre GPUs | Small model is usually enough for metadata Q and A |
| Tool server | find_interface, explain_error, list_failed_messages, downstream_dependencies; approval-gated resend | No configuration changes through the assistant |
| Identity and permissions | PI/PO roles mapped to tool entitlements; flagged interfaces filtered by role | Credentials and secure store never exported |
| Audit | Log of question, tool, message IDs touched and approvals | Every resend recorded with approver |
Security controls mapped to your inputs
| Control | How it is met |
|---|---|
| Data stays on site | Hosting: On-prem server. All exports, stores and inference stay inside your zone. |
| Payload policy | Metadata and error text only by default; masked field extraction only for approved flows. Excluded: Message payloads with personal data, pricing, controlled technical data, channel credentials |
| Role mapping | PI/PO monitoring and configuration roles mapped to tool entitlements for 25 named users. |
| Credentials | Channel credentials and secure store content are never exported or indexed. |
| Write-back | Resend or restart only after named approval and a duplicate-handling check; configuration changes follow your transport process. |
Three-phase rollout
| Phase | Scope | Exit criteria |
|---|---|---|
| 1. Read-only | Interface Q and A over exported metadata for the integration team | Answer accuracy on a fixed question set agreed with business owners; zero authorization leaks in testing |
| 2. Drafts | Triage suggestions on failed messages with cited runbook steps | Drafts accepted without edit at an agreed rate; audit log reviewed |
| 3. Approved actions | Approved resends of specific messages through monitoring functions | Approval workflow tested; rollback and idempotency verified |
Open questions for IT
1. Which PI/PO version and support package, and which monitoring interfaces are available? 2. Which interfaces carry personal or controlled data and must be flagged? 3. Are Java mappings and custom adapter modules documented? 4. How often does the landscape change through transports? 5. Is a migration to SAP Integration Suite planned, and should the graph feed the estimate? 6. Which GPU option (Two to four data-centre GPUs) fits the peak concurrency for 25 users? Use the sizing calculator to check.
Approvals
This is a planning starting point, not a design guarantee. Verify interface availability, object names and licence terms against your exact release and contract before building.
Review of your SAP PI/PO AI blueprint
Optional: send the exported plan and we will comment on the data access path, permissions model and rollout order. The generator works fully without it.
Optional. The tool and every export work without this. No spam.
How to use the generator
Fill the ten fields on the left: company, version, database, hosting model, named users, sites, use cases, data that must never leave the site, GPU availability and target go-live. The plan updates as you type. Be specific in the use cases and protected-data boxes, because those drive the tool list and the exclusions the plan describes. Export the result and mark the open questions that your team cannot answer yet; those become the first workshop agenda.
- Pick the real version, since interfaces differ by release
- List protected data explicitly, one item per line
- Choose Air-gapped if no outbound internet is allowed
- Keep named users realistic, not the licence maximum
What the plan is built on
Every plan follows the same private-AI pattern: read-only access first, a reporting copy or governed interface for heavy questions, a retrieval index over documents with ownership metadata, an open-weight model served locally with vLLM or Ollama, a tool server exposing named read actions, an identity layer that mirrors the system's own permissions, and an append-only audit log. The table rows are specific to SAP PI/PO: they name its real data access mechanisms rather than generic placeholders.
How to read and challenge the result
Treat the components table as a hypothesis. Ask your SAP PI/PO administrators whether each named interface is enabled and licensed, whether the permission model can really be mirrored, and who owns each refresh job. Then walk the rollout table: each phase has exit criteria, and the next phase should not start until the criteria are met. The open-questions block is deliberately uncomfortable; unanswered items are where projects stall.
- Confirm licence terms for every data access path
- Test permissions with a restricted user, not an administrator
- Decide the audit retention period before go-live
- Plan for the next system upgrade from day one
Common mistakes
The most common mistake is giving the model direct database access because it is quick in a demo. It skips the application's own authorization and business logic, and it is hard to defend in a security review. The second is skipping the document index metadata, so a retrieval hit shows content the user cannot open in the source system. The third is starting with write-back. Start read-only, measure accuracy, then add drafts, then approved actions.
Frequently Asked Questions
Does the generated plan require any cloud service?
No. The plan assumes the model, index, tool server and audit log run on your own servers or in your private cloud, and the air-gapped option removes outbound internet entirely. You can still choose to use a cloud service for specific non-sensitive tasks, but the plan does not depend on one.
Is the plan accurate for my exact version?
It is a well-grounded starting point, not a guarantee. Interface availability, support package levels and licence terms vary. Verify each data access path with your administrators and the vendor documentation for your release before committing to a design.
Can I use this for a security review?
Yes, as input. The security controls table maps controls to your inputs, which gives reviewers a concrete starting point. They will add their own requirements, such as logging standards, key management and network segmentation.
What does the GPU choice change?
It changes which model sizes and how many concurrent users you can serve. Use the sizing and value calculator to estimate peak concurrency and GPUs from your own question volumes, then update the plan with the result.
If you want a second pair of eyes on the plan, Netray builds private AI layers on SAP PI/PO and similar on-prem systems and can review your draft with your IT team.
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