Ensemble AI/ML AppKit

Gen 1

Get started with the AI/ML AppKit

The AI/ML AppKit comes pre-configured with everything you need to collect Vibration, Voice and Vision data to feed your machine learning models, as well as a rich collection of demos of various AI use-cases. It features a 4” color LCD, an integrated camera module that can be configured for “selfie” as well as viewfinder orientation, PDM as well as I2S microphones, inertial sensors and more.

Purchase Kit

GitHub

We use GitHub to publish our device driver and OS packs, as well as demo applications, examples and more. You can access our repositories here.

Get Started

Beta AppKit Quick Start Guide (Gen 1)

(v1.2) This Quick Start Guide will get you up and running with your AI/ML AppKit which, with its integrated camera, display, and microphones, is ideal for developing applications using audio, video, or graphics libraries.

Download document

Alif Security Toolkit (ZIP) (Gen 1)

(v0.65) For use with Gen 1 Beta AppKit and Beta VSCode environments only.

Download document

Alif Security Toolkit (tar) (Gen 1)

(v0.65) For use with Gen 1 Beta AppKit and Beta VSCode environments only.

Download document

Beta AI/ML AppKit Pre-Built Demos (Gen 1)

(v1.3) This archive contains pre-built binary files for different AI/ML or graphics demos along with instructions on how to program them into your Beta AI/ML AppKit.

Download document

ML Evaluation Kit GitHub Repo (Gen 1)

(v2.1) This user guide describes the contents of the ML Evaluation Kit Repo which contains source files to build the AI/ML demos in the pre-built demo archive plus additional applications.

Download document

AI/ML Design Flows (Gen 1)

(v1.0) This white paper describes the steps of how a machine learning model that was trained and converted to a TFLite (quantized) format, needs to be further processed so it can take advantage of the Ethos U55 NPU accelerators in Alif Ensemble devices.

Download document

Beta AppKit Schematics (Gen 1)

These are the schematics for the Beta AI/ML AppKit.

Download document

E7 Hardware Reference Manual

(v2.5) Fusion Processor with quad cores up to 160MHz, 400MHz, and 800MHz operation capable of running combinations of Linux and/or RTOS, large memory, secure enclave, many peripherals, and AI/ML NPUs accelerators up to 250 GOPS performance.

Download document

E7 Datasheet

(v2.7) Fusion Processor with quad cores up to 160MHz, 400MHz, and 800MHz operation capable of running combinations of Linux and/or RTOS, large memory, secure enclave, many peripherals, and AI/ML NPUs accelerators up to 250 GOPS performance.

Download document

Ensemble Software Reference Manual

(v1.6) Software Reference manual for the entire family of Ensemble scalable and compatible MCUs and fusion processors.

Get Started

Upgrade to the Gen 2 AI/ML AppKit
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Evaluation Kits

Ensemble AI/ML AppKit

Get started with the AI/ML AppKit

GitHub

We use GitHub to publish our device driver and OS packs, as well as demo applications, examples and more. You can access our repositories here.

Beta AppKit Quick Start Guide (Gen 1)

(v1.2) This Quick Start Guide will get you up and running with your AI/ML AppKit which, with its integrated camera, display, and microphones, is ideal for developing applications using audio, video, or graphics libraries.

Alif Security Toolkit (ZIP) (Gen 1)

(v0.65) For use with Gen 1 Beta AppKit and Beta VSCode environments only.

Alif Security Toolkit (tar) (Gen 1)

(v0.65) For use with Gen 1 Beta AppKit and Beta VSCode environments only.

Beta AI/ML AppKit Pre-Built Demos (Gen 1)

(v1.3) This archive contains pre-built binary files for different AI/ML or graphics demos along with instructions on how to program them into your Beta AI/ML AppKit.

ML Evaluation Kit GitHub Repo (Gen 1)

(v2.1) This user guide describes the contents of the ML Evaluation Kit Repo which contains source files to build the AI/ML demos in the pre-built demo archive plus additional applications.

AI/ML Design Flows (Gen 1)

(v1.0) This white paper describes the steps of how a machine learning model that was trained and converted to a TFLite (quantized) format, needs to be further processed so it can take advantage of the Ethos U55 NPU accelerators in Alif Ensemble devices.

Beta AppKit Schematics (Gen 1)

These are the schematics for the Beta AI/ML AppKit.

E7 Hardware Reference Manual

(v2.5) Fusion Processor with quad cores up to 160MHz, 400MHz, and 800MHz operation capable of running combinations of Linux and/or RTOS, large memory, secure enclave, many peripherals, and AI/ML NPUs accelerators up to 250 GOPS performance.

E7 Datasheet

(v2.7) Fusion Processor with quad cores up to 160MHz, 400MHz, and 800MHz operation capable of running combinations of Linux and/or RTOS, large memory, secure enclave, many peripherals, and AI/ML NPUs accelerators up to 250 GOPS performance.

Ensemble Software Reference Manual

(v1.6) Software Reference manual for the entire family of Ensemble scalable and compatible MCUs and fusion processors.

Upgrade to the Gen 2 AI/ML AppKit
Available Now

Search

Evaluation Kits

Ensemble AI/ML AppKit

Get started with the AI/ML AppKit

GitHub

We use GitHub to publish our device driver and OS packs, as well as demo applications, examples and more. You can access our repositories here.

Beta AppKit Quick Start Guide (Gen 1)

(v1.2) This Quick Start Guide will get you up and running with your AI/ML AppKit which, with its integrated camera, display, and microphones, is ideal for developing applications using audio, video, or graphics libraries.

Alif Security Toolkit (ZIP) (Gen 1)

(v0.65) For use with Gen 1 Beta AppKit and Beta VSCode environments only.

Alif Security Toolkit (tar) (Gen 1)

(v0.65) For use with Gen 1 Beta AppKit and Beta VSCode environments only.

Beta AI/ML AppKit Pre-Built Demos (Gen 1)

(v1.3) This archive contains pre-built binary files for different AI/ML or graphics demos along with instructions on how to program them into your Beta AI/ML AppKit.

ML Evaluation Kit GitHub Repo (Gen 1)

(v2.1) This user guide describes the contents of the ML Evaluation Kit Repo which contains source files to build the AI/ML demos in the pre-built demo archive plus additional applications.

AI/ML Design Flows (Gen 1)

(v1.0) This white paper describes the steps of how a machine learning model that was trained and converted to a TFLite (quantized) format, needs to be further processed so it can take advantage of the Ethos U55 NPU accelerators in Alif Ensemble devices.

Beta AppKit Schematics (Gen 1)

These are the schematics for the Beta AI/ML AppKit.

E7 Hardware Reference Manual

(v2.5) Fusion Processor with quad cores up to 160MHz, 400MHz, and 800MHz operation capable of running combinations of Linux and/or RTOS, large memory, secure enclave, many peripherals, and AI/ML NPUs accelerators up to 250 GOPS performance.

E7 Datasheet

(v2.7) Fusion Processor with quad cores up to 160MHz, 400MHz, and 800MHz operation capable of running combinations of Linux and/or RTOS, large memory, secure enclave, many peripherals, and AI/ML NPUs accelerators up to 250 GOPS performance.

Ensemble Software Reference Manual

(v1.6) Software Reference manual for the entire family of Ensemble scalable and compatible MCUs and fusion processors.

Upgrade to the Gen 2 AI/ML AppKit Available Now

Upgrade to the Gen 2 AI/ML AppKit
Available Now