Multicloud AI & ERP / Cloud AI Applications & Industry AI Solutions
Why it matters
Markets, customers and operations move faster than daily reports. Organizations that see and act on events in seconds catch fraud, prevent outages and capture opportunities their competitors miss.
How it works
From event to action
Live events stream in, AI scores them inside the stream, live dashboards show operators what is happening and automated actions fire when conditions are met, while history lands in storage for analysis and retraining.
AWS, Azure and Google Cloud compared
| AWS | Azure | Google Cloud | |
|---|---|---|---|
| Ingestion | Kinesis Data Streams | Event Hubs, Fabric eventstreams | Pub/Sub |
| Processing | Managed Flink | Fabric Real-Time Intelligence (Eventhouse) | Dataflow |
| Fresh analytics | Redshift streaming ingestion | KQL on Eventhouse | BigQuery continuous queries |
| Automated action | EventBridge | Activator | Eventarc, Pub/Sub |
| Live dashboards | Amazon Quick | Real-Time dashboards, Power BI | Looker |
What makes each cloud different
AWS
On AWS, Kinesis feeds Managed Flink and SageMaker scoring, Redshift streaming ingestion queries seconds-old data and EventBridge triggers downstream systems.
Azure
Fabric Real-Time Intelligence covers the whole flow: eventstreams ingest, Eventhouse analyzes with KQL, dashboards refresh in seconds and Activator takes action.
Google Cloud
On Google Cloud, Pub/Sub and Dataflow process events with in-pipeline models, and BigQuery continuous queries run SQL on rows as they arrive.
Design decisions that matter
- 01Define the decision and its deadline
Seconds, minutes or hours.
- 02Score inside the stream
No round trip to batch systems.
- 03Automate safe actions only
Humans approve the rest.
- 04Keep history for learning
Every event feeds retraining.
Common mistakes we see
- Real-time dashboards nobody acts on. Insight without action.
- Automating risky actions blindly. False positives hurt customers.
- No data quality checks in streams. Bad events trigger bad actions.
A practical 30-day plan
- Week 1
Pick the decision and its event sources.
- Week 2
Stream events and build the dashboard.
- Week 3
Add AI scoring and alerting.
- Week 4
Automate the safest action and measure impact.
How NTS helps
NTS builds real-time analytics and decision platforms on AWS, Microsoft Fabric and Google Cloud, covering event pipelines, AI scoring, live dashboards and automated actions tied to business outcomes.
What you get
- Streaming analytics on live business events
- AI models scoring events in real time
- Live dashboards and alerts
- Decision rules with human oversight
Typical outcomes
- Faster reactions to customers and risks
- Revenue protected by instant decisions
- Live visibility for business leaders
How we work with you
- 1Assess
A focused review of your real-time analytics and AI decisions across AWS, Azure and Google Cloud. We look for the gaps we find most often: real-time dashboards nobody acts on, automating risky actions blindly and no data quality checks in streams.
- 2Design
A target architecture and roadmap built on the decisions that matter most: define the decision and its deadline, score inside the stream, automate safe actions only and keep history for learning.
- 3Build
Hands-on delivery alongside your team. We pick the decision and its event sources, stream events and build the dashboard, add AI scoring and alerting, and finally automate the safest action and measure impact.
- 4Run and improve
We tune models and rules, monitor latency and scale with event volumes.
Why teams choose NTS for real-time analytics and AI decisions
- Act in the moment
We turn live data into immediate decisions.
- Proven streaming patterns
Our designs handle high volumes reliably.
- Explainable decisions
Every automated decision can be traced and reviewed.
Book a free 30-minute review
Talk to an NTS architect about your real-time analytics and AI decisions on AWS, Azure and Google Cloud.