Build GPU-accelerated video AI agents that search, analyze, summarize, and reason over live or recorded video using natural language.
NVIDIA AI Blueprint for Video Search and Summarization (VSS) combines vision-language models, RAG, and NVIDIA NIM microservices to deliver real-time video analytics, visual Q&A, alert verification, clip retrieval, and long-video summarization.
- Search video streams or archives using natural language queries
- Summarize hours of video
- Ask visual questions and automatically generate reports
- Detect and verify real-time alerts with VLMs
🚀 Try the Demo · ⚡ Quickstart · 📚 Documentation · 🏗️ Architecture · 📦 Latest Release
- Overview
- Use Case / Problem Description
- Agent Workflows
- Software Components
- Target Audience
- Repository Structure Overview
- Documentation
- Prerequisites
- Hardware Requirements
- Quickstart Guide
- Contributing
- License
The NVIDIA Blueprint for Video Search and Summarization (VSS) provides a suite of reference architectures for building vision agents and AI-powered video analytics applications. Those architectures bring together accelerated vision microservices, vision language models (VLMs), and large language models (LLMs) so you can use them in existing applications, as standalone microservices, or as part of a larger vision agent.
VSS is organized into three areas of processing and analysis: real-time video intelligence (feature extraction, embeddings, and stream understanding with results published to a message broker), downstream analytics (enrichment of metadata into trajectories, incidents, and verified alerts), and agentic and offline processing (orchestrated tools for search, Q&A, summarization, and clip retrieval, including via the Model Context Protocol).
This repository implements the blueprint and powers the NVIDIA build experience for natural-language video agents—search, summarization, visual Q&A, and related workflows—backed by generative AI, VLMs and LLMs, and