Overview
Metro AI Suite is an application framework with libraries, tools, and reference implementations, to enable partners to create Vision AI and Gen AI solutions in the Safety and Security, Transportation, and Critical Infrastructure markets.
What's New
Announcing Metro AI Suite 2026.0
Metro AI Suite adds real-time Video Search and Summarization with free-text semantic queries, re-identification, and batching controls to detect, classify, and annotate contextual details like license plates. The Smart Traffic Intersection Agent delivers directional density analysis across multi-camera deployments, while the Agentic Predictive Maintenance Pipeline continuously monitors urban infrastructure to detect and alert on critical events and early failures.
Learn MoreIntroducing Intel® Core™ Processor Series 2
Intel® Core™ Series 2 processors bring deterministic, real-time performance to Metro and Smart City deployments — powering multi-camera traffic analytics, urban infrastructure monitoring, and intelligent edge gateways with up to 12 P-cores, ECC memory support, and a 10-year platform lifecycle commitment.
Learn MoreAI Suite Benefits
Pre-built sample pipelines for accelerated application development, performance results to remove ambiguity on hardware choice, and co-marketing opportunities for hardware and software builders.
Validate and Size AI Systems
Identify performance requirements and test hardware configurations on partner-validated AI systems based on x86 architecture
Demonstrate AI Acceleration and Real-Time Performance
Prove viability running real-world AI workloads to balance the right compute, power requirements, and form factors to suit diverse Metro applications.
Develop AI applications faster
Use reference implementations as blueprints for developing AI solutions optimized for Intel® hardware. Or migrate existing systems to Intel® hardware without extensive refactoring.
Technology & Performance
Explore the advanced Vision AI and Gen AI capabilities and video analytics pipelines that enable the Metro AI Suite to deliver proven, repeatable performance on Intel processors at the edge.
Vision AI and Gen AI Capabilities
Discover the underlying technologies that enable Metro AI Suite’s smart city, traffic, and public safety use cases, and benchmarking capabilities to help validate performance.
Vision-Language Models (VLM)
Metro AI Suite integrates VLM capabilities to understand, process, and respond to video-, LiDAR-, and image-based data inputs, enabling complex reasoning with multimodal fusion in the Smart NVR and Video Search and Summarization reference applications.
Metro Vision AI App Recipe
Metro AI Suite employs an integrated, AI-powered solution for modern urban traffic management and monitoring, that enables cities to deploy intelligent systems to see, interpret, and analyze multimodal data from concurrent, live camera feeds to recognize faces, detect objects, see patterns, and create context for public safety and traffic applications.
Sensor Fusion for Traffic Management
Integrating and reconciling data from multimodal sensor inputs, the Metro AI Suite uses frameworks and microservices to process raw sensor data into a unified model for actionable insights. Scenescape combines sensor data into dynamic virtual renderings of buildings, streets, and city grids to enhance monitoring with Digital Twins.
Media Analytics Pipelines
The backbone of the Metro AI suite is the DL Streamer microservice that builds, optimizes, and deploys real-time, multimodal analytics pipelines across multiple, concurrent streams and metadata to power the Smart Intersection and Loitering Detection reference applications.
Metro Gen AI SDK
A comprehensive development environment for optimizing and scaling generative AI applications at the edge using optimized tools and microservices to provide practical question-answering implementation using retrieval-augmented generation (RAG) capabilities.
Visual AI Demo Kit
Enable an end-to-end workflow for processing vision AI media analytics from video ingestion to AI processing, extraction, embedding, data distribution, and real-time visualization of vehicle detection and classification, pedestrian tracking, incident detection, zone-based monitoring, parking spaces, and multi-lane support.
Metro Vision AI SDK
Implement an object detection pipeline with multi-stream video processing, multimodal AI pipelines, and model inference optimization for efficient hardware performance.
Live Video Search
Adapt the Video Search and Summarization pipeline for semantic search on live camera streams, with video indexing with embeddings and timestamped camera metadata, to enable precise selection of camera, time range and free-text queries to retrieve, rank, and play clips with confidence scores. Part of the Live Video Analysis framework.
Live Video Alert Agent
Deploy AI-powered video alerting using OpenVINO VLMs to process real-time streaming protocol (RTSP) streams to generate real-time alerts from natural language prompts and monitor them on a unified dashboard for real time video analytics and safety monitoring. Part of the Live Video Analysis framework.
Live Video Captioning
Live video Captioning deploys AI-powered captioning for live video streams with Deep Learning Streamer (DL Streamer) and OpenVINO™ VLMs for real-time video analytics, accessibility enhancement, performance benchmarking, and intelligent surveillance. Part of the Live Video Analysis framework.
Smart NVR
Use GenAI-powered vision analytics to transform a traditional NVR into a Smart NVR, converting conventional network video recorders into intelligent, context-aware systems, unlocking advanced insights and automation at the edge.
Video Processing for NVR
Process video analytics and transcoding, configure concurrent video processing, including video decode, post-processing, and concurrent display, utilizing the integrated GPU on Intel® Core™ Ultra Processors.
Open Edge Ecosystem
Intel’s empowers partners to seamlessly integrate AI solutions for smart cities, traffic, and security that extend x86 architectures for real-time decision making, improved efficiency, and reduced latency through an open, collaborative approach ensure performance, scalability, and lower overall cost.
Verified AI Edge Systems
Intel partners with OEMs and ODMs to benchmark and verify hardware solutions optimized to meet heterogeneous computing requirements for IoT and AI-driven metro and public safety deployments to ensure optimized hardware and software integration across a range of power levels, sizes and performance options.
Open Edge Platform
A modular, open-source platform to simplify development, deployment and management of edge AI featuring industry-specific building blocks, microservices, frameworks, models, pipelines, and libraries that streamline integration and deployment with cloud-like simplicity and enterprise-grade security to enable infrastructure, applications and efficient AI deployments at scale.
Metro AI Suite SDK
This curated, open-source collection of Vision AI and Gen AI capabilities, reference applications, pipelines, tutorials, and benchmarks ease hardware evaluation and streamline development and deployment of Edge AI solutions for smart cities, traffic, and security, optimized for performance on Intel processors.
Evaluation, Qualification, and Benchmarking
Build and deploy edge AI applications faster with tested, verified, qualified AI Systems, running real-world edge AI workloads, to ensure predictable performance, long-term reliability, and streamlined, scalable deployment.
Intel® ESQ for Intel® AI Edge Systems
This program enables solution builders to test and qualify AI systems running industry AI workloads to prove industrial reliability and viability for powering edge AI innovation.
Metro AI Suite Performance Blueprints
Scaling Vision AI and Gen AI across distributed edge deployments and cloud are a constant tradeoff of efficiency, precision, performance, and cost. Adapting the Metro AI SDK and Suites and Intel systems to industry workloads provides a happy path to selecting a system optimized for the right AI workloads, deployment scenarios, and cost-of-ownership goals.
Visual Pipeline and Platform Evaluation Tool
Analyze throughput, CPU usage, and GPU usage with an open-source tool that enables custom performance benchmarking and KPIs to validate AI inference pipelines to measure latency and resource utilization.
Magic 9 Benchmarks
Visualize what’s possible when comparing generation-to-generation of Intel processors or Intel vs competitors’ processors to understand the differences.
Competitive End-to-end AI and Video Analytics Pipeline Benchmarks
Compare performance differences between Intel® Core™ Processors and competitors’ solutions. (CNDA required)
Intel® Core™ Ultra Processor Series 3 End-to-end AI and Video Pipeline Benchmarks
Measure performance gains of Intel® Core™ Ultra Processor Series 3 over previous generations. (CNDA required)
Reference Applications and Tutorials
The Metro AI Suite features a collection of open-source sample applications and tutorials that demonstrate AI use cases for smart cities, traffic, infrastructure, and public safety.
Smart Intersection
Incorporate real-time, multi-camera scene analysis, and spatial intelligence into traffic management scenarios to understand intersection dynamics and enable pedestrian safety.
Smart Parking
Detect empty parking spaces in real-time with AI-driven video analytics using pre-trained deep learning models and video streams. .
Loitering Detection
Monitor and identify suspicious behavior in real time and proactively address potential security threats with fine-grained detection and streaming video analytics.
Smart Tolling
Revolutionize automated tolling, by fusing multi-camera inputs (Front, Rear, and Side profiles) into a 3D unified view for accurate vehicle and license plate detection and classification, color classification, axle counting and tariffing.
Smart Traffic Intersection Agent
Monitor intersections in real-time with directional traffic density analysis, and Vision Language Model (VLM) powered traffic insights. Manage MQTT traffic data and camera images for intelligent traffic analysis.
Deterministic Threat Detection
Set up and run this Time-Sensitive Networking (TSN) sample application for deterministic, low-latency delivery of AI-processed video and sensor data in a shared network, to protect critical workloads from critical network congestion.
Image Based Video Search
Search live or recorded camera feeds in near real time to detect and retrieve objects of interest from large video datasets, matching objects with location, timestamp, and confidence score details using vector-based search.
Interactive Digital Avatar
Improve user engagement and enable better support with 2D and 3D digital avatars backed by an LLM server to provide real-time intelligent responses to user queries with conversational capabilities.
Visual Search Q&A
Inter a multi-modal search engine with a multi-modal visual Q&A chatbot that answers questions based on search results, and a graphical user interface to ask questions and scan results.
AI Route Planning Agent Tutorial
Finds optimum routes in real-time with AI Agent that fetches and analyzes live feeds from traffic intersections.
AI Smart Intersection Cybersecurity Tutorial
Enable built-in security features to ensure data privacy with strong encryption protocols and blockchain. Learn how to safeguard infrastructure with advanced threat detection to mitigate vulnerabilities across distributed edge devices.
AI Crowd Analytics Tutorial
Use vibe coding to leverage the Metro Vision AI App Recipe to detect and classify objects using pre-configured AI models with customized parameters and develop customized crowd analytics.
