RRepoGEO

REPOGEO REPORT · LITE

amd/RyzenAI-SW

Default branch main · commit 9513bd60 · scanned 6/15/2026, 5:51:52 AM

GitHub: 835 stars · 129 forks

AI VISIBILITY SCORE
35 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
3 / 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 amd/RyzenAI-SW, 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
  • hightopics#1
    Add specific topics to improve categorization

    Why:

    COPY-PASTE FIX
    amd, ryzen-ai, npu, ai-inference, ai-acceleration, machine-learning, deep-learning, examples, demos, tutorials
  • highreadme#2
    Reposition README introduction to emphasize examples for Ryzen AI NPU

    Why:

    CURRENT
    AMD Ryzen™ AI Software includes the tools and runtime libraries for optimizing and deploying AI inference on your AMD Ryzen™ AI based PC. It enables developers to quickly build and run a variety of AI applications for Ryzen™ AI. It is designed with high efficiency and ease-of-use in mind, unleashing the full potential of AI acceleration on Ryzen™ AI. This repository contains the demos, examples and tutorials, demonstrating usage and capabilities of the Ryzen™ AI Software. It is a subset of the Ryzen™ AI Software release.
    COPY-PASTE FIX
    This repository provides **demos, examples, and tutorials** for the AMD Ryzen™ AI Software, enabling developers to optimize and deploy AI inference on **AMD Ryzen™ AI powered PCs**. It showcases how to leverage the Ryzen™ AI NPU for high-efficiency AI acceleration, offering practical guidance for building and running a variety of AI applications.
  • mediumhomepage#3
    Add the official Ryzen AI Software product page as the repository homepage

    Why:

    COPY-PASTE FIX
    Add the official Ryzen AI Software product page URL (e.g., https://www.amd.com/en/technologies/ryzen-ai-software) to the repository's homepage field.

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 amd/RyzenAI-SW
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
NVIDIA TensorRT
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. NVIDIA TensorRT · recommended 1×
  2. openvinotoolkit/openvino · recommended 1×
  3. microsoft/onnxruntime · recommended 1×
  4. pytorch/pytorch · recommended 1×
  5. tensorflow/tensorflow · recommended 1×
  • CATEGORY QUERY
    How can I optimize and deploy AI inference models on my local PC hardware?
    you: not recommended
    AI recommended (in order):
    1. NVIDIA TensorRT
    2. OpenVINO Toolkit (openvinotoolkit/openvino)
    3. ONNX Runtime (microsoft/onnxruntime)
    4. PyTorch JIT (TorchScript) (pytorch/pytorch)
    5. TensorFlow Lite (tensorflow/tensorflow)
    6. Apache TVM (apache/tvm)

    AI recommended 6 alternatives but never named amd/RyzenAI-SW. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools and runtime libraries are available for accelerating AI on client devices?
    you: not recommended
    AI recommended (in order):
    1. ONNX Runtime
    2. TensorFlow Lite
    3. PyTorch Mobile
    4. Core ML
    5. NNAPI
    6. OpenVINO
    7. MediaPipe

    AI recommended 7 alternatives but never named amd/RyzenAI-SW. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    warn

    Suggestion:

  • 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 amd/RyzenAI-SW?
    pass
    AI named amd/RyzenAI-SW explicitly

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

  • If a team adopts amd/RyzenAI-SW in production, what risks or prerequisites should they evaluate first?
    pass
    AI named amd/RyzenAI-SW 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 amd/RyzenAI-SW solve, and who is the primary audience?
    pass
    AI named amd/RyzenAI-SW explicitly

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

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  • Brand-free category queries5 vs 2 in Lite
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