RRepoGEO

REPOGEO REPORT · LITE

antirez/neural-redis

Default branch master · commit fef3d1be · scanned 5/9/2026, 4:27:44 AM

GitHub: 2,227 stars · 101 forks

AI VISIBILITY SCORE
28 /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
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 antirez/neural-redis, 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
    redis-module, neural-networks, machine-learning, in-memory-ml, real-time-ai, online-learning, data-store-ml, redis
  • highreadme#2
    Reposition the README's opening to emphasize its core use case and category

    Why:

    CURRENT
    Neural Redis is a Redis loadable module that implements feed forward neural networks as a native data type for Redis. The project goal is to provide Redis users with an extremely simple to use machine learning experience.
    COPY-PASTE FIX
    Neural Redis is a Redis loadable module that implements feed forward neural networks as a native data type for Redis. It enables **lightweight, in-memory machine learning** by allowing **online training and inference of neural networks directly within the Redis server**. This project aims to provide Redis users with an extremely simple experience for real-time AI applications, especially for **continuous learning on frequently updated application data**.
  • mediumhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://github.com/antirez/neural-redis

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 antirez/neural-redis
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
RedisAI
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. RedisAI · recommended 1×
  2. Apache Ignite · recommended 1×
  3. DeepLearning4j · recommended 1×
  4. TensorFlow · recommended 1×
  5. PyTorch · recommended 1×
  • CATEGORY QUERY
    What tools allow lightweight neural network training and inference directly within an in-memory data store?
    you: not recommended
    AI recommended (in order):
    1. RedisAI
    2. Apache Ignite
    3. DeepLearning4j
    4. TensorFlow
    5. PyTorch
    6. ONNX
    7. OpenVINO
    8. Hazelcast
    9. scikit-learn
    10. Memgraph
    11. MAGE
    12. Tarantool
    13. ONNX Runtime
    14. TinyML frameworks

    AI recommended 14 alternatives but never named antirez/neural-redis. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How to implement continuous learning for small neural networks on frequently updated application data?
    you: not recommended
    AI recommended (in order):
    1. River
    2. TensorFlow Lite
    3. PyTorch Mobile
    4. Keras
    5. Sklearn
    6. Numba
    7. Dask
    8. Ray
    9. Ray Tune
    10. RLlib

    AI recommended 10 alternatives but never named antirez/neural-redis. 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 antirez/neural-redis?
    pass
    AI did not name antirez/neural-redis — 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?

  • If a team adopts antirez/neural-redis in production, what risks or prerequisites should they evaluate first?
    pass
    AI named antirez/neural-redis 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 antirez/neural-redis solve, and who is the primary audience?
    pass
    AI named antirez/neural-redis 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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antirez/neural-redis — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

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  • Brand-free category queries5 vs 2 in Lite
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