Enterprise AI integration
AI inside SAP, Oracle, mainframe and core banking — with zero modifications to the systems of record.
Production-grade integration, full lineage, SOD-compliant. We embed AI capability alongside the systems you already run, mediated through your existing iPaaS — MuleSoft, Boomi, SAP Integration Suite, Oracle Integration Cloud — never directly against the SoR.
Reference architecture
Systems of record
Zero modifications
Integration plane
AI services
SAP → Kafka → AI service → MuleSoft → SAP (audit lineage captured at each hop)
40+
Enterprise integrations delivered
0
SoR code modifications across the estate
11 wk
Median time to first production slice
99.95%
Integration availability target
The integration boundary
Every AI proof-of-concept the team has run has died at the same place.
The model works on the notebook. Landing it inside the SAP, Oracle or mainframe transactional flow without breaking the system of record, the audit trail, the SOD controls, and the batch window is a nine-month integration project no AI vendor has actually scoped or budgeted for. The architect's risk appetite for 'let's just put an AI in front of SAP' is correctly low.
Change Advisory Board friction
Most AI vendors treat CAB approval as a paperwork exercise. In a regulated estate the CAB is the load-bearing control: change-impact assessments, SOD sign-off, regression evidence, batch-window analysis. AI POCs that have not produced any of these documents die at the gate.
Segregation of duties
A model that can post a journal, raise a payment, or transition a claim status crosses SOD boundaries instantly. Without an explicit human-in-the-loop pattern above defined thresholds, the audit team will (correctly) block the production cutover.
Batch window collision
Year-end close, month-end accruals, and overnight settlement runs leave a fragile two- to three-hour window for any new integration. An AI service that adds end-to-end latency or back-pressure into the SoR is one outage away from being switched off.
Audit lineage gaps
For every AI-mediated transaction the audit team needs to reconstruct: which inputs, which model version, which threshold fired, which human reviewed the deferral. Most AI stacks do not capture this; we treat the audit row as a first-class output of every inference.
Architectural principle
Alongside, not inside. AI services run on the customer MLOps platform, exposed via Kafka or REST, and integrated into the SoR through the customer iPaaS with full lineage. The SoR is never directly called by a model.
Integration pattern library
Twelve hardened patterns, by system of record.
Every pattern in this library has shipped in production at a UAE or KSA enterprise. Each one carries a documented control trace and a sample iPaaS flow definition. The downloadable library expands each pattern into a full architecture diagram with Lucidchart, draw.io and Visio source files.
Pattern 01
SAP ECC
BAPI + RFC over SAP JCo
Synchronous decisioning for posting workflows
Pattern 02
SAP S/4HANA
CDS views + OData via SAP Integration Suite
Read-side feature extraction
Pattern 03
SAP (any)
IDoc via Kafka Connect + Debezium
Event-driven document handoff
Pattern 04
SAP S/4HANA
SAP Event Mesh + AEM
Real-time AI scoring on transactional events
Pattern 05
Oracle EBS
Concurrent Programs + OAF over OIC
Batch enrichment without form mods
Pattern 06
Oracle Fusion
Fusion REST + OIC orchestration
Agent copilot embedded in Fusion UX
Pattern 07
IBM i / AS400
Db2 for i + IBM MQ via Boomi
CDC to AI services with replay safety
Pattern 08
z/OS mainframe
z/OS Connect EE + MQ
CICS-mediated decisioning, no mainframe code change
Pattern 09
Temenos T24
T24 IRIS + Kafka
Pre-posting fraud scoring on account opening
Pattern 10
Finacle
Finacle FI/EI + MuleSoft
Arabic OCR into corporate KYC flow
Pattern 11
Murex
Datamart + event publication
Post-trade anomaly detection alongside the book
Pattern 12
Salesforce
Platform Events + REST
Cross-system orchestration with SAP / mainframe
iPaaS coexistence
We plug into yours. We do not replace it.
The integration plane is your decision and your standard. Brocode delivers AI services as platform-agnostic REST and event interfaces; the flow definitions are built inside your iPaaS, in your conventions, by a pod that works alongside your iPaaS team.
- MuleSoft Anypoint
- Boomi
- webMethods
- Apigee
- SAP Integration Suite
- Oracle Integration Cloud
- Azure Integration Services
- Confluent Kafka
- Solace PubSub+
- IBM MQ
- Debezium / Qlik / IIDR
- SAP Event Mesh
Delivery method
Eleven-week median time to first production slice.
Discovery, reference architecture, thin slice, hardening, CAB, cutover, hypercare. The pod is named in the SoW: a Brocode principal enterprise architect, an MLOps lead, and an integration lead. CVs are visible before contract signature.
Week 0–2
Discovery and reference architecture
Brocode principal architect maps the SoR landscape, iPaaS estate, CAB cadence, and SOD constraints. Output: a one-page reference architecture and a documented control-trace pattern signed off by the customer architect.
Named senior pod
Week 3–6
Thin end-to-end slice
One real use case, one real screen, one real data path — built on the customer iPaaS (MuleSoft / Boomi / SAP IS / OIC) with the AI service exposed via REST or events. Full audit lineage from day one.
Live in dev
Week 7–9
Hardening and CAB
Penetration test, performance test, disaster-recovery rehearsal, SOD walkthrough with second-line. CAB submission with change-impact, rollback, and batch-window analysis attached.
CAB-ready evidence
Week 10–11
Cutover and hypercare
Canary cutover during an agreed change window, then hypercare alongside the customer ops team. Brocode owns incident response through the agreed support window before runbook handover.
11-week median go-live
How we compare
The honest table.
Vendor-locked AI add-ons are credible inside their own estates and fragment the moment a non-vendor model is needed. Big-4 SI work is credible on the integration plane and weak on the AI side. Brocode owns both halves of the build with named senior people.
| Capability | Brocode | SAP Joule / BTP AI | Oracle Fusion AI | Salesforce Einstein | Big-4 SI |
|---|---|---|---|---|---|
| Works alongside (not inside) SAP and Oracle | |||||
| Zero code modification on the SoR Brocode publishes a zero-mod commitment with documented edge cases. | Documented policy | ABAP enhancements typical | OAF / Form changes typical | Apex / triggers typical | Varies by partner |
| Plugs into your existing iPaaS | MuleSoft, Boomi, OIC, SAP IS, Azure IS, Kafka | BTP-first | OIC-first | MuleSoft-first within Salesforce | Whatever the customer owns |
| Open-source and best-of-breed models | Subcontracted | ||||
| Named senior architect on contract Brocode publishes the architect CV before SoW signature. | Partner-plus-pyramid | ||||
| Regulator-mapped control trace (CBUAE / SAMA / SOX) Document, posting, and journal-level audit reconstruction by design. | Sometimes | ||||
| Median time to first production slice | 11 weeks | Bound to SAP release | Bound to Oracle release | Bound to Salesforce release | 6–9 months typical |
Objections answered with evidence
Three things every enterprise architect asks. Three production references.
Change control
Touching SAP / Oracle in production needs CAB, change windows and SOD sign-off.
Anonymised UAE tier-1 bank: Arabic OCR and extraction model embedded into the Finacle posting flow via Kafka and MuleSoft. Three point four million account-opening documents per year. Zero ABAP or Finacle code change. Full audit lineage. CBUAE-reviewed.
Existing iPaaS
Are you going to insist on a parallel integration plane?
Anonymised regional utility: predictive maintenance model integrated into SAP IS-U work-order creation via SAP Event Mesh and BAPI orchestration. Built inside the customer SAP Integration Suite, not a parallel plane. Twenty-seven percent reduction in unplanned outages.
Mainframe protection
How do you integrate without disrupting the batch window?
Anonymised insurer: claims-triage model integrated into a mainframe-based policy admin system via z/OS Connect EE and MQ. No mainframe code change. Forty-one percent faster first decision. Brocode worked inside the existing change window owned by the mainframe team.
Free download
AI Integration Pattern Library — 12 Production Blueprints
Fifty-six pages of architecture diagrams, sample iPaaS flow definitions, and the control-trace pattern for SOX, IFRS, CBUAE and SAMA reviews. Drawn from forty-plus enterprise engagements with zero SoR code modifications.
- Pattern 1 — SAP via SAP Integration Suite + Kafka
- Pattern 2 — Oracle via OIC
- Pattern 3 — IBM i / AS400 via Boomi
- Pattern 4 — Mainframe z/OS via MQ
- Patterns 5 to 12 — Temenos, Finacle, Flexcube, Murex, Salesforce
- Sample MuleSoft, Boomi and SAP IS flow definitions
- Control-trace exhibit for SOX / IFRS / CBUAE / SAMA
Frequently asked
What enterprise architects actually want to know.
Every integration is staged through the customer iPaaS rather than calling the SoR directly. Cutover is canary by design: a percentage of traffic moves to the AI-mediated path while the legacy path stays live and reconcilable. Brocode runs a load-and-back-pressure simulation against your real batch profile before the change goes near production, and CAB sees the simulation evidence.
Talk to a principal architect
A senior architect reviews your landscape and replies within one business day.
The architect on your call holds documented SAP / Oracle / mainframe credentials and has shipped at least four enterprise AI integrations into regulated estates in the GCC. CVs are shared before contract signature, never after.
Prefer WhatsApp? Message us with your landscape and we will read it before the call.
Continue exploring
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