Open Edge Platform
An Intel-based, partner-enabled, secure, optimized open platform for the edge to accelerate solution development
Modular and Optimized Edge Software Stack
Open Edge Platform 2026.2 is here
Capabilities Highlights
- Evaluate industry-ready multimodal edge AI use cases optimized with blueprints, reference applications, and pre-built pipelines
- Composable, open-source tools, libraries, and microservices for building multimodal vision AI and Gen AI workflows
- AI inferencing at the edge with popular open source models for Vision AI, Gen AI, and Physical AI, optimized on Intel silicon
Solve the Biggest Challenges at the Edge
Bring industry-ready edge AI to market sooner, with less risk
Enable industry-ready use cases with pre-built sample applications, benchmarks, and demos to evaluate performance and right-size hardware provisioning to avoid guesswork.
Optimize AI Inference at the Edge
Achieve optimal performance with popular Vision AI and Agentic AI models optimized for Intel silicon with the OpenVINO™ toolkit, a built-in runtime and OpenVINO™ Physical AI and OpenVINO™ Gen AI frameworks, for accelerated AI inference.
Make Multi-modal AI easier to operationalize and scale
Accelerate development cycles from prototyping to production with a curated, open-source collection of tools, pipelines, frameworks, microservices and libraries to enable advanced AI functionality and real-time controls.
Edge AI Suites
Accelerate your solution development and optimization with industry-specific Edge AI Suites.
Retail AI Suite
This suite is an open source application framework designed to accelerate AI workload evaluation and hardware selection for retail use cases at the edge. This framework helps retailers assess device configurations across Intel product generations to enhance decision-making and reduce the total cost of ownership.
It includes sample applications for use cases such as:
Self Checkout
- Product recognition (detection, classification, and tracking)
- Full pipeline (product, weight, text, and barcode)
- Age verification
Storewide Loss Prevention
- Fake scans
- Items in the basket
- Multiproduct identification
- Product switching
- Shopper behavior (hiding items)
- Event video summarizationPerson-of-interest re-identification
- Detect and re-identify persons of interest
- Suspicious activity detection
- VLM-powered visual queries and timebound recall
Order Accuracy
- Object detection using multi-camera computer vision
- Smart video analysis and summarization
- Agentic AI workload
- Advanced LVLM Analysis for Fast Food and Dine-in workflows
Voice Enabled Interactions
- Audio capture
- Natural Language processing
- Retrieve information from knowledgebase
- Intelligent “assistance”
- Multi-speaker voice separation
- Face/voice identification
Manufacturing AI Suite
This suite is a powerful toolkit for building and scaling AI in industrial environments. The suite simplifies real-time AI development and deployment by using Edge AI technology from Intel.
It supports predictive maintenance, anomaly detection, quality inspection, worker safety, and more. Developers benefit from tools like IoT protocol support, AI analytics libraries, multicamera system software, and closed-loop AI pipelines. Benchmarking resources help evaluate performance across time series, vision, and GenAI use cases.
Sample Applications
- Predictive maintenance
- Process optimization
- Anomaly detection
- Quality inspection
- Worker safety
- Vision-guided robots
- Operational diagnostics
- Weld defect detection
Tools and Models
- Anomalib Studio
- RF-DETR
- Time Series microservice
- Sensor Fusion
Metro AI Suite
This suite is an application framework with libraries, tools, and reference implementations, enabling partners to create AI solutions in the video safety and security, transportation, and government edge markets.
Some of the Metro AI Suite components include:
AI Apps for any Intel-Based Edge System
- Advanced video search
- Video summarization
- Natural language search
- Intersection management
- Live video stream analysis
- “Live” avatar interaction
- Smart parking
- Smart tolling
- AI transit route system
- Smart intersection
Benchmarks for Real-World Scenarios
- Benchmarking specifications on Intel® AI Edge Systems
- Platform sizing tool
- Smart Buildings Blueprint
- Predictive Maintenance Blueprint
Tools and Software
- AI inference optimization
- Visual and deep learning optimization
- Media processing acceleration
- Edge server video analytics
- Arm* technology to Intel technology conversion
- Sensor fusion-enabled traffic management
- Metro Analytics Catalog
- VMS Plugins
Education AI Suite
This preview collection of education-focused AI applications, libraries, and benchmarking tools demonstrate how audio and video recordings from class sessions can be transformed into concise summaries for use in educational settings. Featuring audio-to-speech (ASR) models optimized on OpenVINO™ and streaming media analytics with intelligent pose detection and re-identification (Re-ID) capabilities in DL Streamer, the suite introduces advanced multimodal pipelines to demonstrate high-performance deployment on Intel® CPUs, integrated GPUs, and NPUs.
Audio Intelligence
- Audio transcription with ASR models (Whisper, Paraformer)
- Summarization with LLMs (Qwen, LLaMA)
- Plug-and-play architecture for integrating new ASR and LLM models
- API-first, design-ready, front-end integration
- Extensible roadmap for real-time streaming, diarization, translation, and video analysis
Video Intelligence
- FLUTTER UI framework
- OCR searching
- Front Camera Pipeline: Student pose detection: sitting, standing, hand raise, leaning
- Rear Camera Pipeline: Re-Identification (ReID) to track students across camera views
- Board Camera Pipeline: Board content Classifications
Robotics AI Suite
Accelerate development adapting physical AI at the edge and explore new functionality with modular, open-source software components to enable fast development of humanoid, autonomous mobile, and stationary robotics. Sample applications with ROS 2 support, demonstrate vision AI, Gen AI, and media analytics pipelines for enabling robotic manipulation, perception, locomotion, and imitation learning with real-time controls. AI inference engines, and hardware-aware tuning enable fast deployment on Intel silicon.
Collection reference applications, libraries, and pipelines for:
Humanoid
- Imitation Learning – ACT
- LLM Robotics Demo
- ROS 2 and Open Standards
- AI Inference engine
- Hardware-aware tuning
- VSLAM: ORB-SLAM3
- Physical AI Studio and OpenVINO Physical AI
- Pi0.5, SmolVLA, LeRobot optimized on Intel
Stationary
- Vision & Control
- Direct-to-kernel model predictive controller
Autonomous Mobile
- ADBScan
- Collaborative SLAM
- Segmentation
- Simulations
- Wandering
- ITFastmapping
- GroundFloor S-Planner
- Multi-camera Demo
- Object Detection
Health and Life Science AI Suite
Combine concurrent tracking of real-time vitals, signal processing into vision AI pipelines. Real-world patient monitoring workloads simulate vitals, track activities, detect health changes with rPPG, and send alerts with validated reference pipelines, using custom datasets and Get-fine-tuned models.
Reference Applications
- Multi‑parameter Monitor: Simulate, analyze, and play back metrics and waveforms
- 3D Visual Tracking: Contactless patient presence and activity monitoring
- AI‑ECG Arrhythmia: Signal‑processing with applied AI
- rPPG: Camera‑based heart and respiration monitoring
- Multimodal Patient Monitoring
- NICU Warmer Monitoring Application
- Surgical endoscopy and instrument tracking pipeline
Models
- Multi-Task Temporal Shift Convolutional Attention Network (MTTS-CAN) model
- Multimodal patient monitoring Data and Control Flows – Metrics Collector Service
- EdgeCrafter and RF-DETR for granular health telemetry and surgical room object tracking
Federal and Aerospace AI Suite
Use capabilities within the Federal and Aerospace AI suite for developing solutions that bring AI to mission –critical use cases including application blueprints to jump start the evaluation of Intel silicon and streamline development of your own custom solutions based on vision AI, language models, and other machine learning tools optimized for Intel hardware. Build with AI libraries tailored to help adapt multi-camera, multi-scene video analytics applications performantly on Intel hardware to improve cost-efficiency and TCO.
Technology and Capabilities
- Multi-modal AI reference
- AI Inference Optimization
- Visual & Deep Learning Optimization
- Media Processing Acceleration
- CUDA to OpenVINO™ compatibity
- Sensor Fusion-Enabled Air Traffic Control
Blueprints
- Enhanced situational awareness for soldier systems and emergency management
- Drone based aerial digital twins powered by Scenescape
- EdgeCrafter and RF-DETR for granular health telemetry and surgical room object tracking
Edge AI Libraries
Composable ingredients for building production-quality multimodal edge AI apps, along with user-friendly workflows for optimizing and deploying models.
- Build edge AI applications and use cases that include vision AI, generative AI (GenAI), and time series AI capabilities.
- Get reusable building blocks, with benchmarks, optimized to run performantly on Intel hardware.
- Shorten app development time and simplify model fine-tuning, retraining, and deployment workflows.
Resources
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