RRepoGEO

REPOGEO REPORT · LITE

IlyaRice/RAG-Challenge-2

Default branch main · commit 452d688d · scanned 5/16/2026, 9:18:05 AM

GitHub: 2,300 stars · 471 forks

AI VISIBILITY SCORE
28 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 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 IlyaRice/RAG-Challenge-2, 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
  • hightopics#1
    Add specific RAG technique topics

    Why:

    COPY-PASTE FIX
    rag, enterprise-rag, rag-challenge, state-of-the-art-rag, pdf-parsing, document-ai, llm-reranking, vector-search, chain-of-thought
  • highabout#2
    Enhance About section description

    Why:

    CURRENT
    Implementation of my RAG system that won all categories in Enterprise RAG Challenge 2
    COPY-PASTE FIX
    Winning solution for the Enterprise RAG Challenge 2, demonstrating state-of-the-art RAG techniques for enterprise document analysis, including custom PDF parsing, parent document retrieval, LLM reranking, and chain-of-thought reasoning.
  • mediumhomepage#3
    Add project homepage URL

    Why:

    COPY-PASTE FIX
    https://abdullin.com/ilya/how-to-build-best-rag/

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 IlyaRice/RAG-Challenge-2
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
run-llama/llama_index
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. run-llama/llama_index · recommended 2×
  2. langchain-ai/langchain · recommended 2×
  3. Pinecone · recommended 2×
  4. deepset-ai/haystack · recommended 1×
  5. weaviate/weaviate · recommended 1×
  • CATEGORY QUERY
    How to build a high-performing RAG system for enterprise document analysis?
    you: not recommended
    AI recommended (in order):
    1. Haystack (deepset-ai/haystack)
    2. LlamaIndex (run-llama/llama_index)
    3. LangChain (langchain-ai/langchain)
    4. Weaviate (weaviate/weaviate)
    5. Pinecone
    6. Elasticsearch (elastic/elasticsearch)
    7. Chroma (chroma-core/chroma)

    AI recommended 7 alternatives but never named IlyaRice/RAG-Challenge-2. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are state-of-the-art RAG techniques for improving context relevance and accuracy?
    you: not recommended
    AI recommended (in order):
    1. sentence-transformers (UKP-SQuARE/sentence-transformers)
    2. Elasticsearch
    3. Pinecone
    4. LangChain (langchain-ai/langchain)
    5. LlamaIndex (run-llama/llama_index)
    6. OpenAI
    7. Neo4j
    8. Vaticle's TypeDB

    AI recommended 8 alternatives but never named IlyaRice/RAG-Challenge-2. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    warn

    Suggestion:

  • 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 IlyaRice/RAG-Challenge-2?
    pass
    AI named IlyaRice/RAG-Challenge-2 explicitly

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

  • If a team adopts IlyaRice/RAG-Challenge-2 in production, what risks or prerequisites should they evaluate first?
    pass
    AI named IlyaRice/RAG-Challenge-2 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 IlyaRice/RAG-Challenge-2 solve, and who is the primary audience?
    pass
    AI did not name IlyaRice/RAG-Challenge-2 — 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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IlyaRice/RAG-Challenge-2 — 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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IlyaRice/RAG-Challenge-2 — RepoGEO report