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Enterprise AI on SAP BTP & AI Core

Fixed-scope 8-12 week AI projects for Canadian enterprises on S/4HANA and RISE with SAP. From procurement automation to predictive maintenance.

What Is SAP BTP AI Consulting?

SAP BTP AI consulting is the design, build, and deployment of AI solutions on SAP Business Technology Platform — using AI Core for ML model training, AI Launchpad for model management, and HANA Cloud as the data layer — to automate business processes within S/4HANA and RISE environments. ChatGPT.ca delivers fixed-scope 8-12 week BTP/AI Core projects for Canadian enterprises, covering procurement automation, natural language reporting, predictive maintenance, and LLM copilots for Fiori.

Why Enterprise SAP AI?

Most SAP customers have the data and the BTP licenses but lack the AI engineering to connect the two. We bridge that gap.

🗄️

Data Silos Across SAP Modules

THE PROBLEM

Your SAP landscape has valuable data trapped in MM, PP, FI, and SD modules that never surfaces in one place. Teams build manual Excel bridges to connect what SAP should connect natively.

OUR SOLUTION

We build AI pipelines on BTP that unify data across SAP modules, giving leadership a single pane of glass with real-time insights.

🧩

BTP Complexity

THE PROBLEM

SAP BTP has 90+ services. Your team licensed it but nobody knows which services to activate, how to connect them, or where AI Core fits into the architecture.

OUR SOLUTION

We design and deploy only the BTP services you actually need — AI Core, AI Launchpad, HANA Cloud — with clear architecture documentation.

🤖

AI Core Learning Curve

THE PROBLEM

AI Core requires ML engineering skills your SAP team doesn't have. Training pipelines, model serving, and inference endpoints feel like a different world from ABAP.

OUR SOLUTION

We handle the ML engineering end-to-end — from model training on your HANA data to production inference via AI Core — and train your Basis team to maintain it.

🇨🇦

PIPEDA Compliance

THE PROBLEM

SAP BTP regions include US and EU but Canadian data residency isn't guaranteed. Regulated industries need proof that PII stays in Canada.

OUR SOLUTION

We architect hybrid deployments that keep sensitive data on Canadian infrastructure while leveraging BTP for compute, ensuring full PIPEDA compliance.

What Can AI Do on SAP?

Six production-ready use cases we deploy on BTP and AI Core

📦

Procurement Automation

AI agents that auto-classify purchase requisitions, match suppliers, flag anomalies, and route approvals — cutting procurement cycle time by 60%.

📊

Natural Language Reporting over HANA

Ask questions in plain English and get instant answers from your SAP data. No more waiting for IT to build custom reports.

🔧

Predictive Maintenance

ML models on AI Core that predict equipment failures from SAP PM sensor data, reducing unplanned downtime by 40%.

⚙️

AI Core ML Pipelines

End-to-end training and serving pipelines on SAP AI Core — demand forecasting, quality prediction, yield optimization.

💬

LLM Copilots for S/4HANA

GPT-powered assistants embedded in Fiori that help users navigate transactions, fill fields, and resolve errors in natural language.

📄

Intelligent Document Processing

Automated extraction of invoices, contracts, and shipping documents into SAP — 95% accuracy with human-in-the-loop for exceptions.

What Are the Architecture Options?

Choose the deployment pattern that fits your compliance and latency requirements

BTP-Native

Full deployment on SAP BTP with AI Core, AI Launchpad, and HANA Cloud. Ideal for greenfield AI projects on RISE.

  • Fully managed by SAP
  • Native S/4HANA integration
  • Single vendor support
Best for: RISE with SAP customers on clean core

Hybrid (Canadian Cloud)

AI models and sensitive data on Canadian AWS/Azure/GCP regions. BTP handles orchestration and S/4HANA integration.

  • Canadian data residency
  • Best-of-breed models
  • PIPEDA by design
Best for: Regulated industries (finance, healthcare, government)

Edge (On-Prem + BTP)

Inference runs on-premise near your SAP ECC/S/4HANA instance. BTP syncs models and aggregates results.

  • Ultra-low latency
  • No data leaves premises
  • Works with ECC
Best for: Manufacturing plants, air-gapped environments

How Does an SAP AI Project Work?

Fixed-scope delivery in 8-12 weeks from assessment to production

Weeks 1-2

Assessment & Discovery

We audit your SAP landscape, BTP entitlements, data quality, and business processes to identify the highest-ROI AI opportunities.

  • SAP landscape assessment
  • AI opportunity matrix
  • Data readiness report
  • Architecture recommendation
Weeks 3-4

Architecture & Proof of Concept

We design the target architecture and build a working PoC on one high-value use case using your real SAP data.

  • Architecture design document
  • Working PoC on real data
  • Performance benchmarks
  • Stakeholder demo
Weeks 5-8

Build & Integrate

Full development of the production solution with BTP/AI Core pipelines, S/4HANA integration, and Fiori front-end.

  • Production AI pipelines
  • S/4HANA integration
  • Fiori UI components
  • Automated testing
Weeks 9-12

Deploy, Train & Handover

Production deployment, user training, Basis team enablement, and documentation for ongoing operations.

  • Production deployment
  • User training sessions
  • Operations runbook
  • 90-day support period

What Results Can You Expect?

Report Generation

Before4-6 hours manual
After30 seconds via NL query
99%

Maintenance Predictions

BeforeReactive (break-fix)
After7-day advance warning
40% less downtime

Procurement Processing

Before3 days per PO cycle
After4 hours automated
85%

Data Analyst Bottleneck

Before2-week report queue
AfterSelf-serve via copilot
Eliminated

Case Study: Canadian Manufacturer on S/4HANA

$2.1M
Annual savings
10 weeks
Time to production
40%
Less unplanned downtime

A mid-market Canadian manufacturer on S/4HANA with 12 production lines was spending $180K/year on reactive maintenance and losing $1.5M annually to unplanned downtime. Their SAP PM data had 3 years of sensor readings that nobody was analyzing.

We deployed predictive maintenance models on SAP AI Core, trained on their historical PM data, with a natural language dashboard on BTP that let plant managers ask questions about equipment health in plain English.

Within 10 weeks, the system was predicting failures 7 days in advance with 89% accuracy. Unplanned downtime dropped 40%, and the maintenance team shifted from reactive to planned work orders — saving $2.1M in the first year.

Technology Stack

SAP BTP
Platform
SAP AI Core
ML Training & Serving
SAP AI Launchpad
Model Management
SAP HANA Cloud
Data Layer
S/4HANA
Business Logic
Python
ML Engineering
LangChain
LLM Orchestration
SAP CAP
Application Layer

Investment

Fixed-scope pricing with no surprises. All projects include architecture, build, deployment, and training.

Discovery & PoC

$25K-$50K

4 weeks

  • SAP landscape assessment
  • AI opportunity matrix
  • Working PoC on real data
  • Architecture recommendation
MOST POPULAR

Full Build

$75K-$250K

8-12 weeks

  • Everything in Discovery
  • Production AI pipelines
  • S/4HANA integration
  • User & Basis team training
  • 90-day support period

Ongoing Retainer

$5K-$15K/mo

Monthly

  • Model retraining & tuning
  • Performance monitoring
  • New use case development
  • Priority support

Frequently Asked Questions

Do we need RISE with SAP to use AI Core?

No. AI Core is available as a standalone BTP service. However, RISE customers get streamlined integration and bundled BTP credits that reduce costs. We work with both RISE and non-RISE environments.

Can you work with our existing SAP ECC system?

Yes. While S/4HANA offers deeper integration, we build AI solutions for ECC environments using BTP as a bridge layer. Many clients start with AI on ECC while planning their S/4HANA migration.

How do you handle Canadian data residency on BTP?

We use hybrid architectures where sensitive data stays on Canadian cloud regions (AWS ca-central-1, Azure Canada Central) while BTP handles orchestration. This ensures PIPEDA compliance without sacrificing BTP capabilities.

What SAP modules do you work with?

We integrate AI across MM (procurement), PP (production), PM (maintenance), FI/CO (finance), SD (sales), and QM (quality). The specific modules depend on your use case — most projects touch 2-3 modules.

Do we need an in-house ML team?

No. We handle all ML engineering and train your SAP Basis team to monitor and maintain the deployed models. For ongoing model retraining, we offer a monthly retainer or can upskill your team to do it independently.

What does the 8-12 week timeline include?

The full timeline covers assessment, architecture, PoC, build, integration, deployment, and training. Simpler use cases (like NL reporting) can ship in 6-8 weeks. Complex multi-module projects may extend to 14 weeks.

Ready to Unlock AI on Your SAP Investment?

Book a free SAP AI assessment. We'll audit your BTP entitlements, evaluate your data readiness, and identify the highest-ROI AI use case for your SAP landscape.

Book SAP AI Assessment