RRepoGEO

REPOGEO REPORT · LITE

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

Default branch main · commit 8f2a1fea · scanned 5/26/2026, 12:56:48 PM

GitHub: 1,450 stars · 307 forks

AI VISIBILITY SCORE
33 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 warn · 0 fail
Objective metadata checks
AI knows your name
2 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface NVIDIA-AI-Blueprints/video-search-and-summarization, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Add a 'What this blueprint is (and isn't)' section to the README

    Why:

    COPY-PASTE FIX
    ### What this blueprint is (and isn't)
This NVIDIA AI Blueprint provides a comprehensive, end-to-end reference architecture for building GPU-accelerated vision agents and AI-powered video analytics applications. It integrates and orchestrates various components, including accelerated vision microservices, VLMs, and LLMs.
**This blueprint is not:**
*   A standalone library like FFmpeg or OpenCV.
*   A low-level deep learning framework like PyTorch or TensorFlow.
*   A cloud-specific service like AWS Rekognition or Google Cloud Video Intelligence API.
Instead, it shows you how to combine and optimize these types of technologies on NVIDIA GPUs to create advanced video intelligence solutions.
  • mediumtopics#2
    Add topics describing the repository's nature as a blueprint/architecture

    Why:

    CURRENT
    agents, llm, rag, skills, video-analytics, video-search, vlm
    COPY-PASTE FIX
    agents, llm, rag, skills, video-analytics, video-search, vlm, reference-architecture, ai-blueprint, solution-accelerator, gpu-accelerated-ai
  • mediumlicense#3
    Clarify the license(s) in the README

    Why:

    COPY-PASTE FIX
    In the 'License' section of the README, add: 'This project is licensed under the terms specified in the `LICENSE` file. Please review the `LICENSE` file for full details on the applicable terms and conditions.'

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface NVIDIA-AI-Blueprints/video-search-and-summarization
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
FFmpeg
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. FFmpeg · recommended 2×
  2. OpenCV · recommended 2×
  3. NVIDIA DeepStream SDK · recommended 2×
  4. PyTorch · recommended 2×
  5. TensorFlow · recommended 2×
  • CATEGORY QUERY
    How can I build an AI system for real-time video search and content summarization?
    you: not recommended
    AI recommended (in order):
    1. FFmpeg
    2. OpenCV
    3. AWS Kinesis Video Streams
    4. Google Cloud Video Intelligence API
    5. AWS Rekognition Video
    6. OpenVINO
    7. NVIDIA DeepStream SDK
    8. Hugging Face Transformers (huggingface/transformers)
    9. PyTorch
    10. TensorFlow
    11. Elasticsearch
    12. PostgreSQL
    13. pgvector (pgvector/pgvector)
    14. Pinecone
    15. Weaviate
    16. Milvus
    17. LangChain
    18. LlamaIndex
    19. OpenAI API
    20. GPT-4
    21. GPT-3.5
    22. Anthropic Claude
    23. Google Gemini
    24. spaCy
    25. NLTK
    26. Flask
    27. Django
    28. Express.js
    29. Gin
    30. Echo

    AI recommended 30 alternatives but never named NVIDIA-AI-Blueprints/video-search-and-summarization. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools help develop GPU-accelerated vision agents for advanced video analytics applications?
    you: not recommended
    AI recommended (in order):
    1. NVIDIA DeepStream SDK
    2. PyTorch
    3. NVIDIA CUDA
    4. cuDNN
    5. TensorFlow
    6. TensorFlow Lite
    7. TensorFlow Serving
    8. OpenCV
    9. NVIDIA TensorRT
    10. FFmpeg
    11. NVIDIA Triton Inference Server

    AI recommended 11 alternatives but never named NVIDIA-AI-Blueprints/video-search-and-summarization. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    pass

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of NVIDIA-AI-Blueprints/video-search-and-summarization?
    pass
    AI named NVIDIA-AI-Blueprints/video-search-and-summarization explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts NVIDIA-AI-Blueprints/video-search-and-summarization in production, what risks or prerequisites should they evaluate first?
    pass
    AI named NVIDIA-AI-Blueprints/video-search-and-summarization explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo NVIDIA-AI-Blueprints/video-search-and-summarization solve, and who is the primary audience?
    pass
    AI did not name NVIDIA-AI-Blueprints/video-search-and-summarization — likely talking about a different project

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

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