Built for Where Industrial AI Is Going
Industrial IoT is shifting from cloud-dependent analytics to on-device intelligence. SensiML enables real-time AI at the sensor endpoint, eliminating cloud latency, connectivity dependencies, and the cost of streaming high-bandwidth sensor data.
Key market drivers
- Predictive maintenance market projected at $21B+ by 2028
- Unplanned downtime costs manufacturers $50B+ annually
- IIoT sensor deployment growing at 22% CAGR
- Regulatory pressure driving continuous monitoring adoption
- Skilled technician shortage accelerating automation demand
Three
Core industrial verticals
Predictive maintenance, process control, and structural health monitoring — each with proven deployments.
Real-time
On-device anomaly detection
No cloud round-trip. Millisecond response for high-speed lines and safety-critical systems.
Legacy+
Over-the-top deployment model
Smart sensor overlay requires no changes to existing PLCs, SCADA, or control networks.
Market Position & Proven Deployments
Predictive Maintenance & Anomaly Detection
SensiML's edge AI models identify early indicators of equipment degradation — motor faults, pump blockage, vibration anomalies — before they escalate into costly failures. The baseline-only training approach eliminates the need to reproduce dangerous fault states, making deployment practical across the full range of industrial machinery. Networks of smart sensor nodes can cover entire factory floors, providing continuous monitoring that spot-check inspection programs simply cannot match.
- Reduces unplanned downtime through early fault detection
- Enables condition-based maintenance, eliminating premature part replacement
- Scales cost-effectively across new and legacy equipment without infrastructure changes
- Validated on pumps, motors, fans, robotic arms, and conveyor systems
Process Control & Quality Monitoring
Intelligent edge sensors transform raw production telemetry into real-time process insight — detecting yield anomalies, isolating out-of-spec product, and triggering control decisions faster than cloud-mediated systems allow. SensiML's compact models filter sensor noise to deliver only actionable events downstream, dramatically reducing data volume while improving signal quality for compliance and reporting systems.
- Real-time quality event detection on high-speed production lines
- Reduces redundant telemetry volume — only insights, not raw streams
- Integrates with legacy SCADA via simple event triggers
- Supports worker ergonomics and safety compliance monitoring via industrial wearables
Structural Health Monitoring
SensiML enables acoustic emission and vibration-based structural monitoring at a cost and scale previously limited to the most critical, high-value infrastructure. Edge AI processing of ultrasonic sensor data detects microscopic material fatigue — the earliest precursor to catastrophic failure — in bridges, pressure vessels, airframes, and industrial facilities. Smart structural sensors replace expensive manual inspection cycles with continuous, autonomous monitoring.
- Detects microscopic crack propagation before macroscopic failure
- Replaces expensive and infrequent manual inspection with continuous monitoring
- Battery-compatible, wireless deployment — no power or wired connectivity infrastructure required
- Applicable to civil infrastructure, industrial vessels, aerospace, and energy assets
Validated Use Cases
Manufacturing
Pump & Motor Fault Detection
Multi-state classification of pump operating conditions including blockage, cavitation, and flow anomalies.
Facilities
Predictive HVAC Maintenance
Acoustic and vibration monitoring of commercial HVAC systems to predict bearing and compressor failures.
Automation
Robotic Arm Integrity Monitoring
Anomaly detection on robotic motion paths — alerting on unintended contact or path deviation.
Worker Safety
Industrial Worker Safety
Wearable-based ergonomics monitoring, fall detection, and compliance tracking for factory floor workers.
Infrastructure
Structural Health Monitoring
Acoustic emission sensing for microscopic crack detection in high-value infrastructure and industrial assets.
Quality
Production Line Anomaly Detection
Real-time isolation of out-of-spec products on high-speed manufacturing lines using vibration and acoustic signatures.
SensiML's industrial edge AI platform combines baseline-only anomaly detection, over-the-top legacy deployment, and a hardware-agnostic model architecture — eliminating the three most common barriers to adoption in industrial accounts. Competitors require fault data collection, infrastructure investment, or silicon-specific deployment. SensiML requires none of these.