RRepoGEO

REPOGEO REPORT · LITE

maderix/ANE

Default branch main · commit d91c9845 · scanned 5/24/2026, 11:33:45 PM

GitHub: 6,680 stars · 920 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 maderix/ANE, 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 disambiguate 'ANE' and improve category visibility

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    apple-neural-engine, ane, machine-learning, deep-learning, backpropagation, reverse-engineering, private-apis, apple-silicon, npu, ml-research, benchmarking
  • mediumreadme#2
    Emphasize research project status earlier in the README

    Why:

    CURRENT
    Training neural networks directly on Apple's Neural Engine (ANE) via reverse-engineered private APIs. No CoreML training APIs, no Metal, no GPU — pure ANE compute.
    COPY-PASTE FIX
    Training neural networks directly on Apple's Neural Engine (ANE) via reverse-engineered private APIs. This is a **research project** demonstrating what's possible, not a production framework. No CoreML training APIs, no Metal, no GPU — pure ANE compute.
  • lowhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    https://github.com/maderix/ANE

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 maderix/ANE
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Core ML
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Core ML · recommended 1×
  2. PyTorch with MPS (Metal Performance Shaders) backend · recommended 1×
  3. TensorFlow with PluggableDevice (for Apple Silicon) · recommended 1×
  4. CoreML · recommended 1×
  5. MLIR (Multi-Level Intermediate Representation) · recommended 1×
  • CATEGORY QUERY
    How can I train neural networks directly on Apple's dedicated AI hardware?
    you: not recommended
    AI recommended (in order):
    1. Core ML
    2. PyTorch with MPS (Metal Performance Shaders) backend
    3. TensorFlow with PluggableDevice (for Apple Silicon)

    AI recommended 3 alternatives but never named maderix/ANE. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking methods to perform deep learning backpropagation on Apple's NPU, bypassing CoreML or GPU.
    you: not recommended
    AI recommended (in order):
    1. CoreML
    2. MLIR (Multi-Level Intermediate Representation)
    3. IREE
    4. Metal Shaders
    5. ONNX Runtime
    6. PyTorch
    7. TensorFlow
    8. Metal Performance Shaders

    AI recommended 8 alternatives but never named maderix/ANE. 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 maderix/ANE?
    pass
    AI named maderix/ANE explicitly

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

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

    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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maderix/ANE — 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