RRepoGEO

REPOGEO REPORT · LITE

alibaba/zvec

Default branch main · commit bae0e1b7 · scanned 5/21/2026, 9:37:53 AM

GitHub: 9,658 stars · 554 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 alibaba/zvec, 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
    Clarify Zvec's in-process, single-machine nature prominently in the README

    Why:

    CURRENT
    Zvec is an open-source, in-process vector database — lightweight, lightning-fast, and designed to embed directly into applications.
    COPY-PASTE FIX
    Zvec is an open-source, **single-machine**, in-process vector database — lightweight, lightning-fast, and designed to embed directly into applications. It excels at providing high-performance, local semantic search capabilities.
  • mediumreadme#2
    Add a 'Comparison to Alternatives' section in the README

    Why:

    COPY-PASTE FIX
    Add the following heading and introductory sentence to the README: `## Why Zvec? Comparison to Alternatives

Zvec stands out among embedded vector databases like Chroma, LanceDB, FAISS, and Hnswlib by offering a unique blend of lightning-fast performance and a lightweight, in-process design, specifically optimized for single-machine applications requiring real-time semantic search.`
  • lowtopics#3
    Add 'high-performance' and 'fast-vector-search' to topics

    Why:

    CURRENT
    agent-skills, db, embedded, faiss, hnsw, llm-memory, local, rag, search-engine, semantic-search, similarity-search, vector-database, vector-db
    COPY-PASTE FIX
    agent-skills, db, embedded, faiss, fast-vector-search, high-performance, hnsw, llm-memory, local, rag, search-engine, semantic-search, similarity-search, vector-database, vector-db

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 alibaba/zvec
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
chroma-core/chroma
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. chroma-core/chroma · recommended 1×
  2. lancedb/lancedb · recommended 1×
  3. facebookresearch/faiss · recommended 1×
  4. nmslib/hnswlib · recommended 1×
  5. milvus-io/milvus · recommended 1×
  • CATEGORY QUERY
    I need an embedded vector database for fast, local semantic search in my application.
    you: not recommended
    AI recommended (in order):
    1. Chroma (chroma-core/chroma)
    2. LanceDB (lancedb/lancedb)
    3. FAISS (facebookresearch/faiss)
    4. Hnswlib (nmslib/hnswlib)
    5. Milvus Lite (milvus-io/milvus)

    AI recommended 5 alternatives but never named alibaba/zvec. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the most performant in-process vector databases for LLM memory and RAG?
    you: not recommended
    AI recommended (in order):
    1. Faiss
    2. Hnswlib
    3. USearch
    4. Annoy
    5. LanceDB
    6. Chroma
    7. Qdrant

    AI recommended 7 alternatives but never named alibaba/zvec. 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 alibaba/zvec?
    pass
    AI named alibaba/zvec explicitly

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

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

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

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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite