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neuralSPOT SDK

Edge AI Made Easy

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neuralSPOT is an open-source, real-time, OS-agnostic SDK for Ambiq’s Apollo SoCs—now with first-class runtime support: TFLM, heliaRT™, and heliaAOT™.

Highlights

01

Accessible

Open source, OS-agnostic, and real-time Al development toolkit built to streamline Al development with Ambiq’s range of ultra-low power SoCs.

02

Customizable

Everything the developer needs to develop, modify, train, and deploy sophisticated features on the Apollo family of SoCs.

03

Easy Profiling

Deploy, Fine Tune, and Profile AI models on all Ambiq development boards.

04

Seamless Prototyping

neuralSPOT streamlines AI features with simple app code, straightforward device I/O, and plug-and-play PC integration.

Bridging the Edge AI Divide

Bridging the Edge AI Divide
neuralSPOT SDK

neuralSPOT SDK

Edge AI Application Prototyping Library Simplifies the embedded development Frees AI Developers to focus on AI

neuralSPOT Autodeploy

neuralSPOT Autodeploy

Easy AI-to-firmware conversion Sophisticated Profiler and Validator Zero friction AI experimentation

Optimized AI Runtimes

Optimized AI Runtimes

neuralSPOT makes choosing a runtime easy by seamlessly integrating LiteRT, heliaRT and heliaAOT

AI Development Kits

heartKIT

  • Detect heart statistics and conditions based on ECG sensor readings
  • Heart Rate, HRV, Afib detection
  • More added regularly

physioKIT

  • Optical-sensor based health statistics
  • SPO2, Heart Rate, Afib, cuff-less blood pressure monitoring

sleepKIT

  • Real-time: Inference is performed in real-time on battery-powered, edge devices
  • Efficient: Leverage modern AI techniques coupled with Ambiq’s ultra-low power SoCs
  • Extensible: Easily add new tasks, models, and datasets to the framework
  • Accurate: Achieve SoTA results with stringent resource constraints

Speech Enhancement

  • Eliminates background noise such as leaf-blowers, music, and restaurant noise from speech
  • Can be used to increase intelligibility and improve speech recognition accuracy

Speaker ID

  • Identifies speech belonging to a specific individual
  • Supports multiple individuals
  • Can be trained on new individuals on-device

AutoDeploy

  • Automatically analyzes, deploys, profiles, and packages AI models for Ambiq devices in a single workflow
  • Converts TFLite models into optimized embedded applications and static libraries
  • Profiles performance, memory usage, and power consumption directly on target hardware

Design Resources

Additional Documentation

  • Set favorites
  • Get update notifications
  • Use search filters

Video Library

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