INTERNET OF MEDICAL THINGS | AGENTIC AI TRANSFORMATION
Can You Detect Your Device Risks Before They Escalate?
Your Devices Signal Risk. Are You Acting Early?
Your medical device data already contains signals across firmware, telemetry, device performance, and fleet-level anomalies. Connected Care Intelligence Layer (CCIL) turns these signals into AI-powered insights within your existing environment—helping teams detect anomalies, investigate risks, and trigger intelligent workflows across Engineering, Quality, Data & IT, and Regulatory.
WHY AREN'T MEDICAL DEVICE MANUFACTURERS GETTING MORE VALUE FROM THEIR DEVICE DATA?
Connected devices generate continuous telemetry across device performance, firmware, connectivity, and data pipelines. Without continuous intelligence, emerging issues can remain hidden until they become investigations or customer complaints.
CCIL helps you:
- Detect what’s changing across your fleet
- Understand why it’s happening
- Act before issues escalate
With AI-powered insights and continuous monitoring, CCIL turns device signals into proactive intelligence.
From
Reactive Monitoring
To
Proactive Intelligence
From
Device-Level Signals
To
Fleet-Wide Visibility
From
Manual Investigation
To
AI-Assisted Investigation
From
Data Collection
To
Actionable Intelligence
WHAT IF YOUR DEVICE DATA COULD TELL YOU WHAT TO DO NEXT?
Meet the Connected Care Intelligence Layer (CCIL)
CCIL turns medical-device telemetry into proactive intelligence, helping teams detect risks earlier, accelerate investigations, & act before issues escalate by continuous fleet monitoring & AI-enabled insights while leveraging their existing environment.
With CCIL, you can:
Identify changes in device telemetry, data quality, and device behaviour before they escalate.
Compare device and firmware cohorts to detect unexpected behaviour & performance issues.
Detect lot-level deviations from expected performance before patterns become widespread.
Use AI-powered analysis to investigate anomalies, identify root causes, & recommend best actions.
Create a unified view of device, telemetry and data health across your connected-device fleet.
Automatically capture anomaly and investigation trails to support quality and regulatory processes.
The result? Earlier detection. Faster investigations. More reliable connected devices.
WHAT CAN CCIL HELP YOU DO?
Connect device data. Detect emerging issues. Turn intelligence into action.
CCIL continuously monitors medical-device telemetry within your existing data environment, helping identify fleet-wide quality, firmware and data-integrity issues — and turning those signals into AI-enabled, actionable insights.
MEET THE CCIL INTELLIGENCE ENGINES
Four intelligence engines to detect emerging device risks, accelerate investigations, and turn telemetry into action.
CCIL continuously monitors medical-device telemetry to identify quality, firmware, and data-integrity issues and transforms those signals into AI-enabled, actionable intelligence.
Problem
Changes in telemetry structure or meaning can go unnoticed until they affect downstream data and analytics.
Signals
Schema, field, structure and telemetry changes across device and vendor cohorts.
AI Actions
Continuously detect schema changes and surface anomalies before they propagate downstream.
Outcomes
Earlier detection of data-integrity risks
HELPS: Data & AI | Engineering
Problem
A manufacturing lot can begin underperforming in the field before the pattern becomes visible through conventional monitoring.
Signals
Device performance deviations across manufacturing lots, cohorts and historical baselines.
AI Actions
Compare lot-level behaviour against expected baselines to identify underperforming cohorts.
Outcomes
Faster identification of emerging quality risks
HELPS: Quality | Engineering | Data & AI
Problem
A firmware release can introduce unexpected behaviour that may remain hidden across a large connected-device fleet.
Signals
Behavioural differences between new firmware cohorts and previously stable releases.
AI Actions
Compare firmware cohorts against established baselines to identify abnormal behaviour early.
Outcomes
Shorter firmware risk exposure
HELPS: Engineering | Quality | Data & AI
Problem
Reconstructing anomaly and investigation history for quality and regulatory processes can require significant manual effort.
Signals
Detected anomalies, timestamps, investigation events and associated telemetry.
AI Actions
Automatically capture detected anomalies and investigation events as traceable records.
Outcomes
Less manual effort for audit readiness
HELPS: Regulatory | Quality | Engineering
WHY NALLAS
We bring 15+ years of experience across product engineering, cloud, data, AI and automation helping enterprises turn complex technology challenges into scalable solutions.
The same intelligence layer can adapt across Medical Devices, Manufacturing, Mining, Energy, Automotive, and Industrial IoT wherever connected devices generate telemetry that needs to be monitored and acted on.
From telemetry ingestion and data engineering to cloud platforms, analytics and Agentic AI, Nallas brings the engineering capabilities needed to build, integrate and operationalize connected-data solutions.
Start with a focused use case, validate the value with your data, and scale what works. Our approach combines reusable accelerators with engineering capabilities to move from pilot → production → continuous intelligence.
Resources
Explore our Resources for insights, tools, and innovation that drive digital transformation. From blogs and case studies to white papers and hackathons, find everything you need to stay ahead. Learn, build, and grow with Nallas.
READY TO DETECT RISKS BEFORE THEY ESCALATE?
The future of connected-device operations is proactive, intelligent, and AI-powered.
CCIL helps medical-device manufacturers turn existing telemetry into AI-powered intelligence and act before issues impact customers.
Talk to our Engineering Expert Team
