RRepoGEO

REPOGEO REPORT · LITE

getnao/nao

Default branch main · commit e4c9db50 · scanned 5/21/2026, 11:32:16 AM

GitHub: 1,187 stars · 157 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 getnao/nao, 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
  • highabout#1
    Update repository description for precise AI categorization

    Why:

    CURRENT
    👾 nao is an open source analytics agent. (1) Create context with nao-core cli, (2) deploy nao chat interface for everyone
    COPY-PASTE FIX
    👾 nao is an open-source AI-powered analytics agent framework for business intelligence, enabling data teams to create context and deploy chat interfaces for data analysis.
  • highreadme#2
    Add explicit license clarification to README

    Why:

    COPY-PASTE FIX
    ## License
nao is released under [specify actual license name(s) here, e.g., 'a custom license combining Apache 2.0 and MIT terms']. Please refer to the `LICENSE` file for full details.
  • mediumreadme#3
    Refine README's 'What is nao?' section to counter miscategorization

    Why:

    CURRENT
    nao is a framework to build and deploy analytics agent. <br/> Create the context of your analytics agent with nao-core cli: data, metadata, modeling, rules, etc. <br/> Deploy a UI for anyone to chat with your agent and run analytics on your data.
    COPY-PASTE FIX
    nao is a framework to build and deploy analytics agents for data analysis and business intelligence. Unlike general web analytics tools or UI libraries, nao focuses specifically on empowering data teams to create robust, AI-driven analytics agents. You can create the context of your analytics agent with nao-core cli (data, metadata, modeling, rules, etc.) and deploy a UI for anyone to chat with your agent and run analytics on your data.

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 getnao/nao
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
langchain-ai/langchain
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. langchain-ai/langchain · recommended 2×
  2. tiangolo/fastapi · recommended 2×
  3. RasaHQ/rasa · recommended 2×
  4. pallets/flask · recommended 2×
  5. run-llama/llama_index · recommended 1×
  • CATEGORY QUERY
    How to build an open-source analytics agent for business intelligence with a chat interface?
    you: not recommended
    AI recommended (in order):
    1. LangChain (langchain-ai/langchain)
    2. LlamaIndex (run-llama/llama_index)
    3. Streamlit (streamlit/streamlit)
    4. Gradio (gradio-app/gradio)
    5. DuckDB (duckdb/duckdb)
    6. PostgreSQL
    7. Haystack (deepset-ai/haystack)
    8. FastAPI (tiangolo/fastapi)
    9. React (facebook/react)
    10. Vue.js (vuejs/core)
    11. Apache Superset (apache/superset)
    12. OpenAI Assistants API
    13. Next.js (vercel/next.js)
    14. ClickHouse (ClickHouse/ClickHouse)
    15. Rasa (RasaHQ/rasa)
    16. Flask (pallets/flask)
    17. Dash (plotly/dash)
    18. Panel (holoviz/panel)
    19. Dask (dask/dask)
    20. LiteLLM (BerriAI/litellm)
    21. Django (django/django)
    22. PowerBI
    23. Tableau

    AI recommended 23 alternatives but never named getnao/nao. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools allow me to deploy a self-hosted text-to-SQL solution for data analysis?
    you: not recommended
    AI recommended (in order):
    1. DB-GPT (eosphoros-ai/DB-GPT)
    2. SQLFlow (sql-flow/sql-flow)
    3. LangChain (langchain-ai/langchain)
    4. Llama 2 (meta-llama/llama-models)
    5. Mistral (mistralai/mistral-src)
    6. Falcon (falconllm/falcon)
    7. Ollama (ollama/ollama)
    8. vLLM (vllm-project/vllm)
    9. Hugging Face Transformers (huggingface/transformers)
    10. T5 (google-research/text-to-text-transfer-transformer)
    11. BART
    12. CodeLlama (facebookresearch/codellama)
    13. Hugging Face Inference Endpoints
    14. FastAPI (tiangolo/fastapi)
    15. Flask (pallets/flask)
    16. Rasa (RasaHQ/rasa)

    AI recommended 16 alternatives but never named getnao/nao. 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 getnao/nao?
    pass
    AI named getnao/nao explicitly

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

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

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

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getnao/nao — 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