RRepoGEO

REPOGEO REPORT · LITE

kendryte/nncase

Default branch master · commit 99431d9d · scanned 5/31/2026, 6:57:28 PM

GitHub: 883 stars · 207 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 kendryte/nncase, 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 sentence to highlight specialization

    Why:

    CURRENT
    `nncase` is a neural network compiler for AI accelerators.
    COPY-PASTE FIX
    `nncase` is an open deep learning compiler stack specifically designed to optimize and deploy neural network models on Kendryte's RISC-V based AI accelerators (K210, K230, K510) and similar embedded edge AI hardware.
  • hightopics#2
    Add specific topics for model formats and target environments

    Why:

    CURRENT
    ai-compiler, compiler, deep-learning, k210, k230, k510, kendryte, llm, neural-network
    COPY-PASTE FIX
    ai-compiler, compiler, deep-learning, k210, k230, k510, kendryte, llm, neural-network, tensorflow-lite, onnx, embedded-ai, edge-ai
  • mediumhomepage#3
    Add a homepage URL to the repository's About section

    Why:

    COPY-PASTE FIX
    https://github.com/kendryte/nncase

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 kendryte/nncase
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
OpenVINO Toolkit
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. OpenVINO Toolkit · recommended 2×
  2. Apache TVM · recommended 1×
  3. TensorRT · recommended 1×
  4. XLA · recommended 1×
  5. Glow · recommended 1×
  • CATEGORY QUERY
    Looking for a deep learning compiler to optimize models for dedicated AI accelerator hardware.
    you: not recommended
    AI recommended (in order):
    1. Apache TVM
    2. TensorRT
    3. OpenVINO Toolkit
    4. XLA
    5. Glow
    6. MLIR

    AI recommended 6 alternatives but never named kendryte/nncase. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Which tools can convert TensorFlow Lite or ONNX models for embedded neural network inference?
    you: not recommended
    AI recommended (in order):
    1. Vela compiler
    2. TensorFlow Lite for Microcontrollers
    3. ONNX Runtime
    4. NVIDIA TensorRT
    5. Edge Impulse
    6. OpenVINO Toolkit
    7. TVM

    AI recommended 7 alternatives but never named kendryte/nncase. 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 kendryte/nncase?
    pass
    AI named kendryte/nncase explicitly

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

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

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

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kendryte/nncase — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite