Ross ROSS = Recommend OSS · open-source software intelligence for agents

NVIDIA-AI-Blueprints/video-search-and-summarization

NVIDIA AI Blueprint for video search and summarization (VSS) is a GPU-accelerated reference architecture for building video analytics agents with real-time verified alerts, visual Q&A, and automated reporting. The VSS Blueprint uses vision language models (VLMs) such as NVIDIA Cosmos, LLMs such as NVIDIA Nemotron, RAG, and NVIDIA NIMs. observed · 2026-08-28

github.com/NVIDIA-AI-Blueprints/video-search-and-summarization · homepage · C++ · NOASSERTION (other) observed · 2026-08-28

Health v2 · maintenance only

83/100

  • Activity 99
  • Release rhythm 82
  • Longevity 48

Flags: no_license

How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.

  • gap_med: 77.5
  • age_days: 680
  • days_rel: 41
  • days_push: 7
  • n_releases_24m: 7

Full methodology

Adoption not part of the score

1824 stars · 378 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

NVIDIA's GPU-accelerated AI Blueprint reference architecture for building video analytics agents that search, summarize, and reason over live or recorded video using natural language. It combines vision-language models (Cosmos), LLMs (Nemotron), RAG, and NVIDIA NIM microservices for real-time alerts, visual Q&A, clip retrieval, and automated reporting.

Use cases

  • search video archives with natural language queries
  • summarize hours of long video footage
  • ask visual questions about video content
  • detect and verify real-time alerts with VLMs
  • build video analytics agents with RAG
  • retrieve relevant video clips automatically
  • generate automated reports from video streams

When to choose

  • building GPU-accelerated video AI agents on NVIDIA infrastructure
  • you need natural-language search and Q&A over live or archived video
  • you want a reference architecture combining VLMs, LLMs, and NIM microservices
  • you need real-time video intelligence with verified alerts and summarization

When to avoid

  • you have no NVIDIA GPU hardware or cloud access
  • you need a lightweight CPU-only video processing pipeline
  • you want a simple end-user app rather than a developer blueprint
  • your use case is unrelated to video understanding or analytics

Facets

framework · maturity active

rag video-processing computer-vision llm-inference agent-framework mcp search-engine nlp computer-vision artificial-intelligence large-language-models cloud self-hosted video-analytics vision-language-models video-summarization nvidia-nim multimodal-ai video-search reference-architecture vision-agents long-video-understanding real-time-alerts video ai-agents retrieval-augmented-generation natural-language-processing gpu docker linux

5 sources

Member repositories

For agents

markdown · JSON · MCP: product_card(name="NVIDIA-AI-Blueprints/video-search-and-summarization")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem