From Alarm Fatigue to Real-Time Insights: A Case Study in AI-Powered Industrial Observability

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From Alarm Fatigue to Real-Time Insights: A Case Study in AI-Powered Industrial Observability

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Case Study

From Alarm Fatigue to Real-Time Insights: A Case Study in AI-Powered Industrial Observability

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access the full case study

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We'd love to brainstorm your priority tech initiatives and contribute to the best outcomes.

From Alarm Fatigue to Real-Time Insights: A Case Study in AI-Powered Industrial Observability

One-liner summary:

ControlRooms.ai partnered with Ideas2IT to build an AI-powered observability platform that ingests terabytes of sensor data, detects anomalies in real-time, and helps plant operators troubleshoot before production is impacted.

The Problem with the Status Quo

Industrial manufacturers lose billions annually to unplanned downtime. Operators often sift through thousands of trends manually and respond only after alarms are triggered. ControlRooms.ai set out to change that by building a cloud-native platform that detects issues before human intervention is needed, using machine learning and continuous data ingestion.

With early traction and fresh funding, they had the vision in place. What they needed was a technology partner to deliver on it.

Where the Gaps Were

To make predictive analytics usable by operators,the platform needed to handle significant complexity:

Stream terabytes of sensor data from IoT devices in near real time
Detect and surface anomalies proactively with minimal false positives
Trigger notifications across channels (web, Teams, email)
Support a multi-tenant architecture for multiple plants and customers
Stay cost-efficient enough to roll out commercially

Commercial cloud platforms could not meet the performance and customization demands. So we built a custom solution from the ground up.

What We Delivered

Ideas2IT designed and implemented a complete observability platform purpose-built for industrial use.

Key Moves:

Built a real-time ingestion pipeline using Azure IoT Hub → Event Hub → Stream Analytics
Deployed AI models (Random Forest + Variational Autoencoder) via Azure ML + AKS for anomaly detection
Developed a fast, resilient backend using FastAPI microservices in Python
Created a visual interface in React and D3 for trend analysis and KPI monitoring
Embedded a robust rule engine (Celery) for real-time alerting via Ably, Sendgrid, and Teams
Architected a secure, multi-tenant setup using TimescaleDB, Istio, Cognito, and Key Vault
Optimized ML pipelines for 70% cost reduction and 400% faster ingestion

The platform was fully containerized, monitored with Datadog, Grafana, and Loki, and designed for scale.

Outcomes We Achieved

KPI	Result
File ingestion speed	400% faster
ML deployment cost	70% lower
Infra cost	300% reduction via smarter multi-tenancy
Historical data query time	<300ms
Time-to-insight	From minutes to seconds

Operators can now detect issues before alarms are triggered. Engineers troubleshoot faster. The ControlRooms.ai team onboards new customers in days, with confidence in production readiness.

Key Takeaways

Sensor data is only useful when delivered in real time and with context
Machine learning models must be production-grade, including validation and alerting
Multi-tenancy is a design requirement

This platform was designed to scale across plants, sectors, and use cases with industrial-grade resilience.

Co-create with Ideas2IT

We show up early, listen hard, and figure out how to move the needle. If that’s the kind of partner you’re looking for, we should talk.

We’ll align on what you're solving for - AI, software, cloud, or legacy systems

You'll get perspective from someone who’s shipped it before

If there’s a fit, we move fast — workshop, pilot, or a real build plan

Trusted partner of the world’s most forward-thinking teams.

Tell us a bit about your business, and we’ll get back to you within the hour.

From Alarm Fatigue to Real-Time Insights: A Case Study in AI-Powered Industrial Observability

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From Alarm Fatigue to Real-Time Insights: A Case Study in AI-Powered Industrial Observability

From Alarm Fatigue to Real-Time Insights: A Case Study in AI-Powered Industrial Observability

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From Alarm Fatigue to Real-Time Insights: A Case Study in AI-Powered Industrial Observability

From Alarm Fatigue to Real-Time Insights: A Case Study in AI-Powered Industrial Observability

Vertical:

Connect with Us

From Alarm Fatigue to Real-Time Insights: A Case Study in AI-Powered Industrial Observability

The Problem with the Status Quo

Where the Gaps Were

What We Delivered

Key Moves:

Outcomes We Achieved

Key Takeaways

Co-create with Ideas2IT