Open Edge Platform ORG

Curated collections of sample applications designed to help you develop optimized AI solutions. Tailored to specific use cases, covering retail, manufacturing, metro, and media & entertainment.

Performance optimized libraries, microservices, and tools to support the development of Edge AI applications.

The Edge Microvisor Toolkit is a streamlined container host that showcases Intel® silicon optimizations. Built on the Azure Linux distribution, it features a Linux kernel maintained by Intel, incorporating all the latest kernel and user patches.

Edge Workloads and Benchmarks are performance-optimized pipelines that leverage the OpenVINO toolkit, the GStreamer multimedia framework, and the Deep Learning Streamer (DL Streamer) for validating media and edge AI analytics benchmarks.

This framework provides a general-purpose toolchain for composing OS images from pre-built artifacts of any Linux distribution that supports Debian or RPM packages. With Image Composer Tool, you can generate edge-optimized OS images using Intel's pre-curated YAML templates or your own customization.

Developer kits reference setup scripts for various kinds of Intel platforms and GPUs

An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference.

Build computer vision models in a fraction of the time and with less data.

Dataset Management Framework, a Python library and a CLI tool to build, analyze and manage Computer Vision datasets.

Deep Learning Streamer (DL Streamer) Pipeline Framework is an open-source streaming media analytics framework, based on GStreamer* multimedia framework, for creating complex media analytics pipelines for the Cloud or at the Edge.

Build computer vision models in a fraction of the time and with less data.

Software Development Kit (SDK) for the Geti™ platform for Computer Vision AI model training.

A comprehensive solution designed to streamline and enhance the deployment and management of infrastructure and applications at the edge

Run Computer Vision AI models with simple Python API and using OpenVINO Runtime

Physical AI Studio is an end-to-end framework for training robots to perform tasks through imitation learning from human demonstrations.

Multimodal object tracking and scene analytics for highly actionable, real-world contextualized data

Open Edge Platform: Edge Orchestrator Web-UI

The Edge AI Tuning Kit is a comprehensive solution for creating, tailoring, and implementing AI models in the edge platform.

Edge Node Onboarding and Provisioning services

Virtual Edge Node onboarding and deployment scripts and configurations

Agents installed as system services in the Edge Node OS

Edge-optimized immutable Edge Microvisor Toolkit, integrated with Kubernetes and foundational extensions

Edge Orchestrator documentation includes deployment, user, developer, and contribution guides; and API references, tutorials, troubleshooting, and software architecture specifications.

Helm charts for deploying Edge Infrastructure Manager services

Manages deployment services and application lifecycles for cloud-native applications across distributed edge networks.

Trusted Compute is a set of software defined security extensions that utilize hardware security capabilities of the Edge Node within the Open Edge Manageability Framework.

Core services for the Edge Infrastructure Manager

Shared code and library resources used by orchestrator components

A collection of cloud-native applications that facilitate the deployment of Edge Nodes in the Edge Platform

Edge Infrastructure Managers for communication with Edge Nodes

Extensions for the Edge Infrastructure Manager

Oversees management services for clusters, including monitoring and operation.

Facilitates catalog services for application packaging and deployment.

Central hub for shared continuous integration (CI) workflows and actions for the Open-Edge-Platform project

Manages metadata across multiple Orchestrator services.

Offers testing frameworks for cluster management.

Ensures access to edge clusters.

Observability Tenant Controller service maintains multitenancy configuration for Observability (o11y) services on Edge Orchestrator.

Utilities of Edge Manageability Framework Orchestrator

The Application Orchestrator Tenant Controller is a Kubernetes Deployment of a Go server that handles lifecycle management for multi-tenancy Projects.

This repository provides key Observability Helm Charts and its helper applications deployable on the Edge Orchestrator.

Provides Intel-specific API support for clusters.

Edge Microvisor Update Tool

Alerting Monitor service handles management of alert notifications in the Edge Orchestrator.

SRE Exporter service enables exporting Edge Orchestrator's Service Level Indicators (SLIs) and its key runtime metrics to external systems.

Open Edge Platform Command Line Interface

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A modular framework for few-shot visual segmentation using visual prompting techniques. Enables easy experimentation with different algorithms, backbones (SAM, MobileSAM, DinoV2), and pipeline components for finding and segmenting objects from just a few examples.

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A research tool for exploring and annotating large datasets with Active Learning

The Edge AI Sizing Tool is designed to showcase the scalability and performance of AI use cases on edge devices.

Run and evaluate your edge system with the Intel® ESQ command-line tool.

Edge-Desktop-Virtualization has essential components for the IDV use case, leveraging Intel's graphics and display virtualization technology (Graphics SR-IOV) on cloud/edge-native infrastructure (k3s/k8s/kubevirt)).

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A public-facing, centralized place to store reusable workflows and actions used by Geti projects.

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