RRepoGEO

REPOGEO REPORT · LITE

swirlai/swirl-search

Default branch main · commit 69452b80 · scanned 5/14/2026, 9:57:15 PM

GitHub: 3,013 stars · 286 forks

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 swirlai/swirl-search, 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 the README H1/H2 to emphasize federated orchestration

    Why:

    CURRENT
    <h1>SWIRL</h1>

## Give your team ChatGPT-level search without moving data to the cloud
    COPY-PASTE FIX
    <h1>SWIRL: Federated AI Search & RAG Orchestrator</h1>

## Get instant, secure answers from all your company's knowledge without moving data
  • mediumreadme#2
    Add explicit comparison to traditional search engines and vector databases

    Why:

    CURRENT
    The "Why SWIRL?" section implicitly compares via a table but does not name alternatives.
    COPY-PASTE FIX
    In the "Why SWIRL?" section, add: "Unlike traditional search engines (Elasticsearch, Solr) or vector databases (Pinecone, FAISS) that require data ingestion and indexing, SWIRL acts as a federated orchestrator, querying your existing data sources in place."
  • lowtopics#3
    Add more specific topics for enterprise and data federation

    Why:

    CURRENT
    ai-search, bigquery, django, federated-query, federated-search, gpt, large-language-models, metasearch, python, rag, relevancy, retrieval-augmented-generation, search, search-engine, unified-search
    COPY-PASTE FIX
    ai-search, bigquery, django, enterprise-search, data-federation, federated-query, federated-search, gpt, large-language-models, metasearch, python, rag, relevancy, retrieval-augmented-generation, search, search-engine, unified-search

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 swirlai/swirl-search
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Elasticsearch
Recommended in 3 of 2 queries
COMPETITOR LEADERBOARD
  1. Elasticsearch · recommended 3×
  2. Hugging Face Transformers · recommended 1×
  3. FAISS · recommended 1×
  4. Annoy · recommended 1×
  5. HNSWlib · recommended 1×
  • CATEGORY QUERY
    How to implement RAG on internal company data without moving it to the cloud?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers
    2. FAISS
    3. Annoy
    4. HNSWlib
    5. Llama.cpp
    6. Ollama
    7. Elasticsearch
    8. PostgreSQL
    9. pgvector
    10. Chroma
    11. Weaviate
    12. sentence-transformers/all-MiniLM-L6-v2
    13. BAAI/bge-small-en-v1.5

    AI recommended 13 alternatives but never named swirlai/swirl-search. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What's an easy way to deploy AI-powered search across enterprise applications quickly?
    you: not recommended
    AI recommended (in order):
    1. Elasticsearch
    2. Azure Cognitive Search
    3. Pinecone
    4. Apache Solr
    5. Elasticsearch
    6. Vespa.ai
    7. Algolia

    AI recommended 7 alternatives but never named swirlai/swirl-search. 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 swirlai/swirl-search?
    pass
    AI named swirlai/swirl-search explicitly

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

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