AI-guided edge ML for sensor products
Build production edge AI from real sensor data — without the expert bottleneck.
SensiML combines time-series data tools, AI-guided workflows, efficient AutoML, and vendor-agnostic C firmware generation so embedded teams can deploy sensor intelligence on resource-constrained devices.
Multi-sensor data · AI-guided workflow · Efficient model selection · Low memory and latency · Readable C firmware · MCU-class deployment
The Challenge
Cloud AI tools aren't built for the edge
General-purpose ML frameworks ignore the unique constraints of sensor data, tight memory budgets, and microcontrollers. SensiML was purpose-built to solve exactly this.
✓ With SensiML
AutoML automates data labeling, feature extraction, and model optimization end-to-end. Ship deployment-ready code that runs efficiently on edge processors from 64-bit MPUs down to 8-bit MCUs — with best-in-class accuracy.
✗ Without SensiML
Months of manual dataset manipulation, feature engineering, and edge model optimization. Cloud frameworks generate bloated models. Engineers spend more time fighting tools than building products. Inference accuracy suffers at the edge.
How It Works
From sensor data to deployed AI in 4 steps
The Analytics Toolkit handles every stage of your ML pipeline — so you focus on your product, not ML infrastructure.
Collect & label
Capture, manage, and label both real and synthetically generated train/test sensor data with Data Studio. Label events with an intuitive visual interface — no scripting needed.
Auto-build model
Analytics Studio runs AutoML — testing hundreds of algorithm combinations and automatically selecting the best for your device constraints.
Generate firmware
Knowledge Pack outputs optimized C/C++ inference code targeted to your specific MCU, processor, and OS — ready to compile.
Test & deploy
Validate models, then ship. Continue improving models on-device as new data arrives in the field.
Optional AI Assist Mode
Instruct expert AI agent workers to build your model for you. Via a simple chat interface, utilize SensiML's pre-trained AutoML agents to perform some or all of the Analytics Toolkit workflow steps for you.
Use Cases
Built for the sensor applications that matter
SensiML powers recognition tasks across many edge AI use cases where cloud-dependent AI simply isn't an option.
Acoustic event detection
Detect machine faults, glass breakage, infant cries, or custom sounds on battery-powered devices.
Activity recognition
Classify movement, gait cycles, ergonomics, and exercise types from wearable or embedded motion sensors.
Anomaly detection
Catch equipment faults before they fail. Enable predictive maintenance across machinery and infrastructure.
Gesture recognition
Add intuitive gesture control to automotive, industrial machinery, and smart consumer devices.
Keyword spotting
Deploy custom wake words and voice commands on ultra-low-power devices without cloud connectivity.
Vibration classification
Monitor transportation, heavy machinery, and infrastructure for vibration signatures that signal failure.
Why SensiML
The only AutoML platform purpose-built for edge sensors
Not adapted from cloud tools — designed from the ground up for microcontrollers and real-world sensor data.
Runs on any hardware
From 8-bit MCUs to ARM Cortex-M, RISC-V, ESP32, AI accelerators, and larger edge processors. Supports 20+ silicon platforms including Arm, Espressif, Infineon, Intel, Microchip, NXP, Nordic, and ST.
Full pipeline automation
AutoML handles feature engineering, model selection, hyperparameter tuning, and firmware generation — eliminating months of manual work.
Deployment-ready output
Knowledge Packs output optimized C/C++ code tailored to your device — not generic Python notebooks you have to convert yourself.
Sensor-native algorithms
Algorithm libraries built specifically for time-series sensor data — not repurposed from image or NLP models that don't fit your use case.
Open-source option
Piccolo AI offers the industry's first open-source AutoML for edge IoT — hardware-agnostic and freely available on GitHub.
Latest AI features
Analytics Studio AI Assist provides a natural chat interface to automate model building using expert agents. Data Studio's GenAI voice tool creates hyper-realistic synthetic speech datasets — dramatically accelerating voice model development.
Ready to ship smarter sensor products?
Start free with Piccolo AI or unlock the full Analytics Toolkit.