RRepoGEO

REPOGEO REPORT · LITE

deepsense-ai/ragbits

Default branch main · commit 32074a71 · scanned 6/30/2026, 9:01:41 PM

GitHub: 1,651 stars · 139 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 deepsense-ai/ragbits, 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's main tagline to explicitly state it's a RAG framework.

    Why:

    CURRENT
    *Building blocks for rapid development of GenAI applications*
    COPY-PASTE FIX
    *A comprehensive RAG framework and toolkit for building and evaluating scalable GenAI applications.*
  • mediumtopics#2
    Add "rag-framework" and "rag-toolkit" to topics.

    Why:

    CURRENT
    agents, document-search, evaluation, guardrails, llms, optimization, prompts, rag, vector-stores
    COPY-PASTE FIX
    agents, document-search, evaluation, guardrails, llms, optimization, prompts, rag, vector-stores, rag-framework, rag-toolkit
  • lowreadme#3
    Add a dedicated "Why Ragbits?" section highlighting its RAG evaluation focus.

    Why:

    COPY-PASTE FIX
    ## Why Ragbits?

Ragbits stands out with its **strong emphasis on integrated RAG evaluation tools and metrics**. We position evaluation as a first-class citizen, providing built-in functionalities to systematically test, benchmark, and improve your RAG pipelines from day one.

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 deepsense-ai/ragbits
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LlamaIndex
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. LlamaIndex · recommended 1×
  2. LangChain · recommended 1×
  3. Haystack · recommended 1×
  4. RAGatouille · recommended 1×
  5. Weaviate · recommended 1×
  • CATEGORY QUERY
    Seeking a toolkit for developing scalable GenAI RAG applications supporting various document types.
    you: not recommended
    AI recommended (in order):
    1. LlamaIndex
    2. LangChain
    3. Haystack
    4. RAGatouille
    5. Weaviate
    6. OpenSearch
    7. Amazon Kendra

    AI recommended 7 alternatives but never named deepsense-ai/ragbits. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What framework allows swapping LLMs and vector stores for flexible RAG application development?
    you: not recommended
    AI recommended (in order):
    1. LangChain (langchain-ai/langchain)
    2. LlamaIndex (run-llama/llama_index)
    3. Haystack (deepset-ai/haystack)
    4. LiteLLM (BerriAI/litellm)
    5. Ragas (Ragas-AI/ragas)

    AI recommended 5 alternatives but never named deepsense-ai/ragbits. 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 deepsense-ai/ragbits?
    pass
    AI named deepsense-ai/ragbits explicitly

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

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

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

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deepsense-ai/ragbits — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite