RRepoGEO

REPOGEO REPORT · LITE

unum-cloud/USearch

Default branch main · commit 9fd6b011 · scanned 5/24/2026, 9:57:02 PM

GitHub: 4,115 stars · 318 forks

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 unum-cloud/USearch, 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 README H1/H3 to explicitly state category and competitors

    Why:

    CURRENT
    <h1 align="center">USearch</h1> <h3 align="center"> Smaller & <a href="https://www.unum.cloud/blog/2023-11-07-scaling-vector-search-with-intel">Faster</a> Single-File<br/> Similarity Search & Clustering Engine for <a href="https://github.com/ashvardanian/numkong">Vectors</a> & 🔜 <a href="https://github.com/ashvardanian/stringzilla">Texts</a> </h3>
    COPY-PASTE FIX
    <h1 align="center">USearch: Universal Vector Search & Clustering Engine</h1> <h3 align="center"> A Faster, Smaller, and Multi-Language Alternative to Faiss, Hnswlib, and Annoy for Approximate Nearest Neighbor Search and Clustering of Vectors & Arbitrary Objects </h3>
  • mediumreadme#2
    Add a 'Comparison with Alternatives' section to README

    Why:

    COPY-PASTE FIX
    A new section in the README, e.g., '## Comparison with Alternatives', that briefly outlines how USearch differentiates itself from Faiss, Hnswlib, Annoy, ScaNN, Milvus, and Weaviate in terms of performance, memory footprint, multi-language support, and ease of embedding.
  • lowtopics#3
    Add 'multi-language' and 'cross-platform' to topics

    Why:

    CURRENT
    approximate-nearest-neighbor-search, clustering, database, faiss, full-text-search, fuzzy-search, image-search, kann, nearest-neighbor-search, recommender-system, search, search-engine, semantic-search, simd, similarity-search, text-search, vector-search, webassembly
    COPY-PASTE FIX
    multi-language, cross-platform, approximate-nearest-neighbor-search, clustering, database, faiss, full-text-search, fuzzy-search, image-search, kann, nearest-neighbor-search, recommender-system, search, search-engine, semantic-search, simd, similarity-search, text-search, vector-search, webassembly

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 unum-cloud/USearch
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Faiss
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Faiss · recommended 2×
  2. Hnswlib · recommended 2×
  3. Annoy · recommended 2×
  4. ScaNN · recommended 2×
  5. Milvus · recommended 2×
  • CATEGORY QUERY
    What's a fast open-source library for vector similarity search across multiple programming languages?
    you: not recommended
    AI recommended (in order):
    1. Faiss
    2. Hnswlib
    3. Annoy
    4. ScaNN
    5. Milvus
    6. Weaviate

    AI recommended 6 alternatives but never named unum-cloud/USearch. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Need an efficient engine for approximate nearest neighbor search and clustering large vector datasets.
    you: not recommended
    AI recommended (in order):
    1. Faiss
    2. Hnswlib
    3. Annoy
    4. ScaNN
    5. Weaviate
    6. Milvus

    AI recommended 6 alternatives but never named unum-cloud/USearch. 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 unum-cloud/USearch?
    pass
    AI named unum-cloud/USearch explicitly

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

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

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

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