RRepoGEO

REPOGEO REPORT · LITE

amd/gaia

Default branch main · commit 373b40a3 · scanned 6/23/2026, 1:41:49 AM

GitHub: 1,458 stars · 123 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
40 /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
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/gaia, 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
    Reposition the README's opening statement to explicitly counter miscategorizations and highlight its core value

    Why:

    CURRENT
    **GAIA** is AMD's open-source framework for building intelligent AI agents that run **100% locally** on AMD Ryzen AI hardware. Keep your data private, eliminate cloud costs, and deploy in air-gapped environments—all with hardware-accelerated performance.
    COPY-PASTE FIX
    Unlike general-purpose web frameworks or cloud-dependent AI solutions, **GAIA** is AMD's open-source framework for building intelligent AI agents that run **100% locally** on AMD Ryzen AI hardware. Keep your data private, eliminate cloud costs, and deploy in air-gapped environments—all with hardware-accelerated performance.
  • highabout#2
    Update the repository description to be more specific about its local, privacy-first nature

    Why:

    CURRENT
    Build AI agents for your PC
    COPY-PASTE FIX
    Build privacy-first, 100% local AI agents for your PC, optimized for AMD Ryzen AI hardware.
  • mediumtopics#3
    Expand repository topics to include more specific terms for local AI agents and LLMs

    Why:

    CURRENT
    agents, ai, aipc, amd, genai, local, privacy, ryzenai
    COPY-PASTE FIX
    ai-agents, local-ai, llm-agents, offline-ai, privacy-first, amd, ryzen-ai, genai, aipc

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/gaia
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LM Studio
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. LM Studio · recommended 1×
  2. Ollama · recommended 1×
  3. LocalAI · recommended 1×
  4. LangChain · recommended 1×
  5. Haystack · recommended 1×
  • CATEGORY QUERY
    How can I develop AI agents that run entirely on my own PC for privacy?
    you: not recommended
    AI recommended (in order):
    1. LM Studio
    2. Ollama
    3. LocalAI
    4. LangChain
    5. Haystack
    6. PrivateGPT
    7. Hugging Face Transformers

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

    Show full AI answer
  • CATEGORY QUERY
    What framework allows building performant generative AI models directly on local hardware?
    you: not recommended
    AI recommended (in order):
    1. PyTorch
    2. TensorFlow
    3. JAX
    4. ONNX Runtime
    5. MXNet
    6. DeepSpeed

    AI recommended 6 alternatives but never named amd/gaia. 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 amd/gaia?
    pass
    AI named amd/gaia 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/gaia in production, what risks or prerequisites should they evaluate first?
    pass
    AI named amd/gaia 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/gaia solve, and who is the primary audience?
    pass
    AI named amd/gaia explicitly

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

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amd/gaia — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite