RRepoGEO

REPOGEO REPORT · LITE

swirlai/swirl-search

Default branch main · commit 055e31c6 · scanned 6/25/2026, 11:57:14 AM

GitHub: 3,031 stars · 285 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)

3 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 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
    Strengthen README's opening paragraph to emphasize secure, no-data-movement enterprise RAG

    Why:

    CURRENT
    ### Open-source federated metasearch and RAG over your enterprise sources — without moving your data.
    COPY-PASTE FIX
    Swirl Community Edition is an open-source federated metasearch and RAG platform designed for secure enterprise search. It enables instant, AI-powered answers from your company's knowledge across 100+ apps, critically, without moving your data and while keeping it secure. Deploy in minutes, not months.
  • mediumtopics#2
    Add enterprise-focused and security-related topics

    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, federated-query, federated-search, gpt, large-language-models, metasearch, python, rag, relevancy, retrieval-augmented-generation, search, search-engine, secure-search, unified-search, data-security, knowledge-management
  • lowreadme#3
    Add a 'Comparison to Alternatives' section in the README

    Why:

    COPY-PASTE FIX
    ## 🆚 Comparison to Alternatives

Unlike traditional enterprise search solutions or RAG frameworks that often require data movement or extensive indexing, Swirl provides an open-source, federated metasearch and RAG engine that operates directly over your existing enterprise APIs and data sources. This unique approach ensures data remains secure and in place, offering a distinct advantage over systems like Elasticsearch, Coveo, or LlamaIndex for organizations prioritizing data sovereignty and rapid deployment without ETL.

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 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Elasticsearch · recommended 2×
  2. Google Cloud Search · recommended 2×
  3. Vertex AI · recommended 2×
  4. Coveo · recommended 2×
  5. Microsoft Purview eDiscovery (Premium) · recommended 1×
  • CATEGORY QUERY
    How can I implement secure enterprise search and RAG across diverse data sources without data movement?
    you: not recommended
    AI recommended (in order):
    1. Microsoft Purview eDiscovery (Premium)
    2. Microsoft Graph Connectors
    3. Microsoft Copilot for Microsoft 365
    4. Elastic Stack
    5. Elasticsearch
    6. Kibana
    7. Beats
    8. Logstash
    9. Google Cloud Search
    10. Vertex AI
    11. Coveo
    12. Sinequa
    13. OpenText IDOL

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

    Show full AI answer
  • CATEGORY QUERY
    What tools enable unified search with LLM-powered result re-ranking over existing enterprise APIs?
    you: not recommended
    AI recommended (in order):
    1. Coveo
    2. Elasticsearch
    3. LlamaIndex
    4. LangChain
    5. Algolia
    6. OpenSearch
    7. Azure Cognitive Search
    8. Azure OpenAI Service
    9. Google Cloud Search
    10. Vertex AI
    11. PaLM 2
    12. Gemini

    AI recommended 12 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 named swirlai/swirl-search 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
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