RRepoGEO

REPOGEO REPORT · LITE

airweave-ai/airweave

Default branch main · commit c0519299 · scanned 5/20/2026, 1:46:29 PM

GitHub: 6,347 stars · 787 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
33 /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
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 airweave-ai/airweave, 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
    Add a clear disclaimer in the README to disambiguate the brand name

    Why:

    CURRENT
    The current README starts with a logo and then 'Open-source context retrieval layer for AI agents and RAG systems.'
    COPY-PASTE FIX
    Add a clear, concise disclaimer immediately after the main tagline in the README, e.g., 'Note: Airweave is an AI infrastructure project and is not affiliated with any sleep product companies.'
  • mediumabout#2
    Refine the repository description to reinforce purpose and disambiguate

    Why:

    CURRENT
    Open-source context retrieval layer for AI agents
    COPY-PASTE FIX
    Airweave: An open-source context retrieval layer for AI agents and RAG systems, connecting LLMs to enterprise data. (Not affiliated with sleep product companies.)
  • mediumreadme#3
    Add a 'Comparison to Alternatives' section in the README

    Why:

    COPY-PASTE FIX
    ## Comparison to Alternatives

Airweave provides a complete context retrieval layer, differentiating itself from vector databases like Weaviate, Milvus, FAISS, and Annoy by offering a full API, data connectors, and agent-specific features beyond just raw vector search. While these tools excel at similarity search, Airweave focuses on the end-to-end retrieval pipeline for AI agents and RAG systems, including pre-processing, chunking, metadata management, and integration with various enterprise data sources.

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 airweave-ai/airweave
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
facebookresearch/faiss
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. facebookresearch/faiss · recommended 1×
  2. spotify/annoy · recommended 1×
  3. nmslib/hnswlib · recommended 1×
  4. weaviate/weaviate · recommended 1×
  5. milvus-io/milvus · recommended 1×
  • CATEGORY QUERY
    What are good open-source tools for context retrieval in RAG systems?
    you: not recommended
    AI recommended (in order):
    1. FAISS (facebookresearch/faiss)
    2. Annoy (spotify/annoy)
    3. Hnswlib (nmslib/hnswlib)
    4. Weaviate (weaviate/weaviate)
    5. Milvus (milvus-io/milvus)

    AI recommended 5 alternatives but never named airweave-ai/airweave. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I connect AI agents to enterprise data for accurate information retrieval?
    you: not recommended
    AI recommended (in order):
    1. Azure AI Search

    AI recommended 1 alternative but never named airweave-ai/airweave. 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 airweave-ai/airweave?
    pass
    AI named airweave-ai/airweave explicitly

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

  • If a team adopts airweave-ai/airweave in production, what risks or prerequisites should they evaluate first?
    pass
    AI named airweave-ai/airweave 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 airweave-ai/airweave solve, and who is the primary audience?
    pass
    AI did not name airweave-ai/airweave — 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?

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airweave-ai/airweave — 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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