Multicloud AI & ERP / Cloud AI Applications & Industry AI Solutions
Why it matters
Unplanned downtime, scrap and missed deliveries cost manufacturers dearly. Predictive maintenance and AI quality inspection help, but only when insights flow into the systems that schedule work and order parts.
How it works
From shop floor to top floor
Machines and sensors feed industrial data platforms with asset models that give readings context. AI models predict failures, detect defects and optimize yield, and results flow into ERP and MES systems as work orders and schedule changes.
AWS, Azure and Google Cloud compared
| AWS | Azure | Google Cloud | |
|---|---|---|---|
| Industrial data | AWS IoT SiteWise | Azure IoT Operations, Fabric | Manufacturing Data Engine |
| Edge processing | IoT Greengrass, SiteWise Edge | IoT Operations on Arc | Manufacturing Connect, Distributed Cloud |
| Visual inspection | Rekognition Custom Labels | Azure AI Vision | Visual inspection with Vertex AI |
| SAP integration | SAP on AWS, AppFlow | SAP on Azure, Logic Apps connectors | SAP on Google Cloud, Cortex Framework |
| Engineer assistant | Bedrock agents | Factory operations agents, Copilot | Gemini assistants |
What makes each cloud different
AWS
AWS IoT SiteWise collects and models industrial data, with SiteWise Edge working offline in the plant, SageMaker for predictive models and strong SAP-on-AWS integration.
Azure
Azure IoT Operations runs on Arc-enabled Kubernetes in the plant, Fabric analyzes telemetry and Dynamics 365 and SAP on Azure connect insights to supply chain and maintenance.
Google Cloud
Google's Manufacturing Data Engine contextualizes plant data in BigQuery, and the Cortex Framework brings SAP data alongside it quickly for combined analytics and AI.
Design decisions that matter
- 01Asset models first
Context turns readings into insight.
- 02Edge for real-time control
Cloud for analytics and training.
- 03Close the loop into ERP
Predictions become work orders.
- 04Start with one line and one problem
Prove value, then scale.
Common mistakes we see
- Dashboards without actions. Predictions nobody uses.
- Ignoring OT security. Connected plants become targets.
- Pilots that never scale. No standard data model across plants.
A practical 30-day plan
- Week 1
Pick one line and one costly failure mode.
- Week 2
Connect machines and build the asset model.
- Week 3
Train a predictive or inspection model.
- Week 4
Connect to ERP to create work orders automatically.
How NTS helps
NTS delivers manufacturing AI on AWS, Azure and Google Cloud, covering industrial data platforms, predictive maintenance, AI inspection and SAP integration, with OT security designed in.
What you get
- Predictive maintenance for equipment
- Quality inspection with computer vision
- AI connected to SAP and ERP data
- Supply chain forecasting
Typical outcomes
- Less unplanned downtime
- Fewer defects reaching customers
- Smarter inventory and supply planning
How we work with you
- 1Assess
A focused review of your manufacturing and ERP AI across AWS, Azure and Google Cloud. We look for the gaps we find most often: dashboards without actions, ignoring OT security and pilots that never scale.
- 2Design
A target architecture and roadmap built on the decisions that matter most: asset models first, edge for real-time control, close the loop into ERP and start with one line and one problem.
- 3Build
Hands-on delivery alongside your team. We pick one line and one costly failure mode, connect machines and build the asset model, train a predictive or inspection model, and finally connect to ERP to create work orders automatically.
- 4Run and improve
We monitor models on the shop floor and expand to new lines and plants.
Why teams choose NTS for manufacturing and ERP AI
- Factory to cloud
We connect plant data to cloud AI securely.
- ERP integration know-how
We work with SAP and other enterprise systems.
- Practical results
We focus on downtime, quality and inventory.
Book a free 30-minute review
Talk to an NTS architect about your manufacturing and ERP AI on AWS, Azure and Google Cloud.