RRepoGEO

REPOGEO REPORT · LITE

ruvnet/RuVector

Default branch main · commit 87399fa7 · scanned 5/22/2026, 5:07:12 AM

GitHub: 4,118 stars · 518 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 ruvnet/RuVector, 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

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Clarify 'Ru' in RuVector to prevent misinterpretation

    Why:

    COPY-PASTE FIX
    Add a sentence early in the README, for example: 'Note: 'Ru' in RuVector refers to its Rust implementation, not the Russian language.'
  • highreadme#2
    Reinforce 'on-device AI inference' and 'self-optimizing' in the README's opening

    Why:

    CURRENT
    The self-learning, self-optimizing vector database — with graph intelligence, local AI, and PostgreSQL built in.
...runs AI models right on your hardware — no cloud APIs, no per-query bills, GPUs optional, CPUs preferred.
    COPY-PASTE FIX
    Replace or rephrase the initial positioning in the README to clearly state: 'RuVector is the self-learning, self-optimizing vector database designed for high-performance, real-time **on-device AI inference**. It integrates graph intelligence and local AI capabilities, running directly on your hardware (CPUs preferred, GPUs optional) without cloud APIs or per-query bills.'

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 ruvnet/RuVector
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Neo4j
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Neo4j · recommended 1×
  2. Weaviate · recommended 1×
  3. Milvus · recommended 1×
  4. Zilliz Cloud · recommended 1×
  5. Chroma · recommended 1×
  • CATEGORY QUERY
    Seeking a self-optimizing vector database with graph intelligence for local AI applications.
    you: not recommended
    AI recommended (in order):
    1. Neo4j
    2. Weaviate
    3. Milvus
    4. Zilliz Cloud
    5. Chroma

    AI recommended 5 alternatives but never named ruvnet/RuVector. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are high-performance real-time vector GNN databases for on-device AI inference?
    you: not recommended
    AI recommended (in order):
    1. Faiss
    2. Hnswlib
    3. USearch
    4. SQLite
    5. vss0
    6. sqlite-vss
    7. Milvus Lite
    8. ScaNN

    AI recommended 8 alternatives but never named ruvnet/RuVector. 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 ruvnet/RuVector?
    pass
    AI named ruvnet/RuVector explicitly

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

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

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

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ruvnet/RuVector — 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