SensiML brings real-time event detection to the IoT sensing endpoint with software usable by developers regardless of AI/ML skill level. Models are created using SensiML’s AutoML analytics engine that automatically generates an optimized, device-ready model maximizing accuracy within the specified resource constraints of the target hardware.
Resulting models are automatically translated into embedded code (with options for binary, library, or full source output) delivering real-time inferencing that executes directly on the target device itself… not in the cloud. The result is smart applications that run faster, provide insight where events occur, require less network performance, and are more secure through better partitioning of data processing tasks.
SensiML’s AI software suite brings the firmware and data science expertise so that you can go from proof-of-concept to production rapidly and with confidence.
Transform Your IoT Device From Merely Connected to Truly Intelligent
SensiML’s platform brings the firmware and data science expertise so that you can go from PoC to production rapidly and with confidence.
Significant Benefits for IoT Product and Application Development
Significant Time-To-Market Gains: 5x faster development over hand-coded algorithms
AI Without Data Science Complexity: AutoML tool usable by mainstream developers
Runs on MCUs: Enabling practical AI application on embedded wireless IoT devices
Maximize Your Hardware: Smart compilation optimizes for MCU, DSP, and FPGA
Extensibility and Flexibility: Add algorithms, change hardware, customize code as desired
Proven Solution: Launched in 2016 by Intel, now independent and greatly expanded
Platform independence: Hardware-, JVM- and OS-independent, optimized for use in embedded edge platforms such as gateways and hub devices. Runs on more than 40 different types of gateway and is ported and optimized for many JVMs, operating systems and hardware configurations.
“The integration with SensiML Analytics Studio and Google’s TensorFlow Lite for Microcontrollers provides a nice end-to-end workflow for creating IoT edge models on embedded devices”
Ian Nappier
TensorFlow Lite for Microcontrollers Product Manager at Google
To enable high-quality data, SensiML’s Data Capture Lab is expressly built to enable collection, cleansing, labeling, and management of train and test datasets using a rigorous workflow supporting one to many users.
The SensiML Knowledge Pack consists of the complete code required to transform raw sensor into classified insights as trained from datasets and ground truth labels you supply for your application.
The SensiML Knowledge Pack consists of complete code required to transform raw sensor into classified insights as trained from datasets and ground truth labels you supply for your application.
SensiML covers a broad array of embedded microcontrollers and sensors enabling developers to target the right system for their application needs. From small ultra-low power MCUs possessing tens of kB memory to multi-core x86 client nodes with GBs of SRAM, SensiML provides ML code output to suit the hardware capabilities of your chosen platform.
Whether you are an experimenter, startup, mid-sized manufacturer, or large enterprise, SensiML has a plan tailored to suit your requirements. Compare our different plan features or get started with our "Free Community Edition" to determine what is best for your own IoT project. As such, you can fully explore the capabilities of the toolkit, collect and label your own data, and build and show real working AI edge models!
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