RRepoGEO

REPOGEO REPORT · LITE

akshata29/entaoai

Default branch main · commit aa6cfbfb · scanned 6/3/2026, 6:13:42 PM

GitHub: 865 stars · 244 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 akshata29/entaoai, 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 README opening to emphasize "enterprise RAG accelerator"

    Why:

    CURRENT
    This sample demonstrates a few approaches for creating ChatGPT-like experiences over your own data.
    COPY-PASTE FIX
    This accelerator provides a comprehensive solution for creating ChatGPT-like experiences over your own enterprise data, enabling secure chat and Q&A.
  • mediumtopics#2
    Add solution-oriented topics to improve category visibility

    Why:

    CURRENT
    azure, azure-functions, azure-openai, azure-webapp, azureopenai, chatgpt, cognitive-search, gpt-3, gpt-35-turbo, langchain, openai, pinecone, redis-search, vector-store
    COPY-PASTE FIX
    azure, azure-functions, azure-openai, azure-webapp, azureopenai, chatgpt, cognitive-search, gpt-3, gpt-35-turbo, langchain, openai, pinecone, redis-search, vector-store, enterprise-rag, chatbot-solution, custom-data-qa, generative-ai-accelerator
  • lowhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://github.com/akshata29/entaoai

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 akshata29/entaoai
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Azure OpenAI Service
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Azure OpenAI Service · recommended 2×
  2. Azure AI Search · recommended 2×
  3. Elasticsearch · recommended 2×
  4. Azure Active Directory · recommended 1×
  5. Azure Private Link · recommended 1×
  • CATEGORY QUERY
    How to build a secure chatbot for internal enterprise documents using generative AI?
    you: not recommended
    AI recommended (in order):
    1. Azure OpenAI Service
    2. Azure AI Search
    3. Azure Active Directory
    4. Azure Private Link
    5. Azure Policy
    6. AWS Bedrock
    7. Amazon Kendra
    8. AWS Identity and Access Management
    9. AWS Virtual Private Cloud
    10. Google Cloud Vertex AI
    11. Google Cloud Search
    12. Google Cloud IAM
    13. Google Cloud VPC Service Controls
    14. Hugging Face Transformers (huggingface/transformers)
    15. Elasticsearch
    16. OpenSearch
    17. Keycloak
    18. Okta
    19. LangChain (langchain-ai/langchain)
    20. LlamaIndex (run-llama/llama_index)
    21. OpenAI API
    22. Anthropic API
    23. Cohere API
    24. PostgreSQL
    25. MongoDB

    AI recommended 25 alternatives but never named akshata29/entaoai. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are effective strategies for RAG with custom data using vector stores and cognitive search?
    you: not recommended
    AI recommended (in order):
    1. Azure AI Search
    2. Azure OpenAI Service
    3. Pinecone
    4. LangChain
    5. OpenAI
    6. Anthropic
    7. Weaviate
    8. LlamaIndex
    9. Elasticsearch
    10. Chroma
    11. Qdrant

    AI recommended 11 alternatives but never named akshata29/entaoai. 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 akshata29/entaoai?
    pass
    AI named akshata29/entaoai explicitly

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

  • If a team adopts akshata29/entaoai in production, what risks or prerequisites should they evaluate first?
    pass
    AI named akshata29/entaoai 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 akshata29/entaoai solve, and who is the primary audience?
    pass
    AI did not name akshata29/entaoai — 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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