Back to SAP S/4HANA Plugin Platform
For Chief Information Officers

Deploy AI
Without Infrastructure
Chaos.

One MTA file. One command. Twelve minutes. Four AI engines running inside your SAP S/4HANA. No GPU clusters. No data science teams. No ABAP modifications. No architecture review.

12 min
Deploy Time
0 GPU
Infrastructure Needed
100%
Clean Core Compliance
0 ABAP
Modifications Required
100% Clean Core
Zero ABAP
Zero GPU
SAP BTP Certified
SOC 2 Type II
The Infrastructure Problem

Why AI Projects Fail
Before They Start

You know AI can transform your SAP operations. The problem is the 18-month, $2M implementation project that stands between the idea and the result.

AI Projects Requiring GPU Clusters & Data Science Teams

Every AI vendor promises transformation — then hands you a requirements document for $500K in GPU infrastructure, a 6-person data science team, 6 months of data labeling, and a pipeline architecture that makes your solutions architect cry.

$500K+
Typical AI infra cost/year

SAP Modifications Breaking Clean Core

Custom BAdIs, Z-tables, ABAP reports, kernel modifications. Every one is technical debt. Every one breaks during upgrades. Every one violates SAP's Clean Core strategy — the strategy your board just approved last quarter.

6-18 mo
Typical upgrade remediation

Integration Hell with Third-Party Tools

Each new tool needs its own middleware, its own authentication flow, its own data pipeline, its own monitoring stack. Your integration landscape looks like a plate of spaghetti — and every new strand increases your attack surface.

47%
CIO time on integration issues

6-Month AI Deployment Timelines

Requirements gathering. Architecture review. Security assessment. Procurement. Infrastructure provisioning. Data engineering. Model training. UAT. Go-live. By the time the AI is deployed, the business problem has changed twice.

6-18 mo
Typical AI project timeline
12-Minute Deployment

ONE File. ONE Command.
Twelve Minutes. Done.

No consultants. No project plan. No architecture review board. Your team can deploy this during a lunch break.

01

Receive ONE MTA File

A single .mtar binary containing all four AI engines, the Fiori dashboard, license agent, SAP Joule agents, HANA table definitions, XSUAA roles, Event Mesh subscriptions, and Fiori tile configurations.

12-18 GB compiled binary — 8 layers of IP protection, no source code

02

Run ONE Command

cf deploy zynoviq-sap-plugin.mtar — that is the entire deployment. SAP BTP Cloud Foundry handles service creation, binding, routing, and health checks automatically.

Zero ABAP transports. Zero custom tables. Zero configuration files.

03

AI Auto-Discovers Your System

The auto-discovery engine reads your SAP metadata, generates vector embeddings for your specific configuration, loads pre-trained models, and activates all four engines. Zero manual setup.

12 minutes from command to fully operational AI — tested and verified

$ cf deploy zynoviq-sap-plugin.mtar

That is the entire deployment command. SAP BTP Cloud Foundry handles service creation, HANA table provisioning, XSUAA binding, Event Mesh subscription, Fiori tile registration, and health check verification. Automatically.

100% SAP Clean Core

100% Clean Core Compliance.
By Architecture, Not by Promise.

Not "mostly Clean Core" or "Clean Core compatible." Structurally impossible to violate Clean Core — the architecture does not permit kernel modifications.

Event-Driven Architecture

Subscribes to SAP Event Mesh for real-time transaction events. Never modifies the source system. Pure observer pattern.

Read-Only OData Access

All SAP data access via standard OData V4 APIs. No custom RFC calls, no direct table reads, no ABAP function modules.

Zero ABAP Modifications

Not a single line of ABAP. No BAdIs, no enhancements, no Z-tables, no custom transports. Your S/4HANA kernel is untouched.

BTP-Native Deployment

Runs entirely on SAP BTP Cloud Foundry. Uses SAP HANA Cloud, SAP Event Mesh, SAP XSUAA, SAP Destination Service — all standard SAP services.

Standard SAP Security Model

XSUAA roles, OAuth 2.0 flows, SAP Identity Authentication Service integration. No custom authentication schemes.

Zero-Impact Uninstall

cf undeploy removes everything — HANA tables, services, configurations, Fiori tiles. Zero residual artifacts in your SAP landscape.

What This Means for Your Upgrade Path

When SAP releases S/4HANA 2025 or 2026, you apply the upgrade to your core system. Zynoviq continues running on BTP — completely unaffected. No regression testing against our code. No transport remediation. No "will this break our custom ABAP?" conversations. Because there is no custom ABAP.

Zero-Training AI Architecture

No GPU Clusters. No Data Scientists.
No Training Data Needed.

The 7-Layer Accuracy Stack achieves 98.7% accuracy on Day 1 using CPU-only inference, purpose-built AI engines, and deterministic mathematical analysis.

1
Purpose-Built AI Engines85-97%

Zynoviq purpose-built AI engines — OSI-approved, CPU-only inference

2
Chain-of-Thought Prompting+3-5%

Step-by-step reasoning templates engineered for financial analysis

3
Few-Shot Examples+2-3%

Real-world fraud, compliance, and supply chain examples embedded in prompts

4
RAG Context Injection+2-4%

Your SAP data + industry benchmarks injected as prompt context — no fine-tuning

5
Deterministic Tool Calling100%

IEEE 754 double-precision for all financial math — zero LLM approximation

6
Unsupervised Anomaly Detection+3-5%

IsolationForest, DBSCAN, Z-Score, Benford's Law — pure mathematical analysis

7
Cross-Module Correlationx1.4

Multi-engine signal fusion — when 3 engines flag same entity, confidence multiplies

Why This Matters for CIOs

GPU Infrastructure
$50K-500K/year$0
Data Science Team
3-6 FTEs ($600K+/yr)0 FTEs
Training Data Preparation
3-6 months0 days
Model Training Time
2-8 weeks0 minutes
Time to First Result
6-18 months12 minutes
AI Engines (All OSI-Approved)
Zynoviq Reasoning Engine

Complex financial reasoning, Chain-of-Thought analysis

Zynoviq NLU Engine

Fast classification, threshold detection, pattern matching

Zynoviq Classification Engine

Multilingual voice processing, NER for SAP entities

Infrastructure Economics

Total Infrastructure Cost:
Built for Enterprise Budgets.

Customer deploys on their own BTP tenant. Zero new infrastructure to provision. Zero GPU. Zero additional servers. The AI runs on standard SAP BTP resources.

SAP BTP ServiceMonthly CostNote
SAP HANA Cloud (shared)IncludedStandard BTP entitlement
SAP Event MeshIncludedStandard messaging tier
Cloud Foundry RuntimeIncluded2 GB memory allocation
SAP XSUAA + DestinationIncludedIncluded with BTP
Total Zynoviq InfrastructureContact SalesAll 4 engines included
Traditional AI Infrastructure
GPU clusters: $50,000-$500,000/year
Data science team: $600,000+/year (3-6 FTEs)
Data engineering pipeline: $200,000/year
ML operations platform: $100,000/year
Total: $950,000-$1,400,000/year
Zynoviq SAP S/4HANA Plugin
GPU clusters: $0 (CPU-only inference)
Data science team: $0 (zero-training architecture)
Data engineering pipeline: $0 (auto-discovery)
ML operations platform: $0 (self-managing)
Total: A fraction of traditional AI infrastructure costs
Security Architecture

Zero-Trust. Data Sovereign.
Built for Your Security Review.

Every security control your CISO will ask about is already built in. Here is the architecture that passes enterprise security reviews.

Zero Trust

Zero-Trust Architecture

Every API call authenticated. Every request authorized. No implicit trust between components. Micro-service isolation with per-service XSUAA scopes.

Data Sovereign

100% Data Sovereignty

All AI inference runs inside your SAP BTP tenant. Zero external API calls for data processing. The only outbound call: license validation (32-character ID, no business data).

RSA-4096

RSA-4096 License Signing

License tokens signed with RSA-4096 private keys. BTP fingerprint bound — cannot be copied to another tenant. Tamper detection on every validation.

SHA-256

SHA-256 Audit Trail

Every AI decision, every compliance check, every fraud flag — hashed and chained. Immutable 7-year retention. Tamper-proof by mathematics.

AES-256

AES-256 Encryption at Rest

All HANA Cloud tables encrypted with AES-256. All sensitive configuration encrypted in SAP Credential Store. Zero plaintext secrets anywhere.

SOC 2

SOC 2 Type II Compliant

Full audit trail for all 5 Trust Service Criteria — Security, Availability, Processing Integrity, Confidentiality, Privacy.

What Your Team Avoids

Everything You Don't
Have to Build

No GPU procurement or provisioning
No data science hiring or contracting
No ML pipeline architecture design
No data labeling or training data preparation
No model training or hyperparameter tuning
No ABAP development or transport management
No custom table creation or schema design
No middleware integration layer
No authentication framework development
No monitoring stack configuration
No data export pipeline engineering
No vendor cloud security assessment
See It Live

Schedule a
Technical Deep Dive

Bring your solutions architect. We will walk through the MTA structure, the BTP deployment topology, the Clean Core compliance verification, and the security architecture. Forty-five minutes. Zero slides.

12-Minute Deploy
Zero GPU Required
100% Clean Core
Enterprise-Friendly Pricing
SOC 2 Type II