RRepoGEO

REPOGEO REPORT · LITE

timescale/pgai

Default branch main · commit 3e054856 · scanned 5/13/2026, 5:16:31 AM

GitHub: 5,797 stars · 310 forks

AI VISIBILITY SCORE
35 /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
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 timescale/pgai, 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's opening to clarify library's unique value

    Why:

    CURRENT
    A Python library that transforms PostgreSQL into a robust, production-ready retrieval engine for RAG and Agentic applications.
    COPY-PASTE FIX
    A Python library that transforms PostgreSQL into a robust, production-ready retrieval engine for RAG and Agentic applications, offering advanced features like automatic vector embedding synchronization and a Semantic Catalog for natural language to SQL, building on and extending `pgvector`.
  • mediumhomepage#2
    Add project homepage to About section

    Why:

    COPY-PASTE FIX
    https://timescale.com/pgai
  • lowtopics#3
    Expand repository topics with more specific keywords

    Why:

    CURRENT
    ai, llm, postgresql, rag
    COPY-PASTE FIX
    ai, llm, postgresql, rag, vector-embeddings, semantic-search, text-to-sql, python-library, pgvector

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 timescale/pgai
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
pgvector/pgvector
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. pgvector/pgvector · recommended 1×
  2. sqlalchemy/sqlalchemy · recommended 1×
  3. psycopg/psycopg2 · recommended 1×
  4. psycopg/psycopg · recommended 1×
  5. langchain-ai/langchain · recommended 1×
  • CATEGORY QUERY
    Seeking a Python library to manage vector embeddings and RAG within a PostgreSQL database.
    you: not recommended
    AI recommended (in order):
    1. pgvector (pgvector/pgvector)
    2. SQLAlchemy (sqlalchemy/sqlalchemy)
    3. psycopg2 (psycopg/psycopg2)
    4. psycopg3 (psycopg/psycopg)
    5. LangChain (langchain-ai/langchain)
    6. LlamaIndex (run-llama/llama_index)
    7. Qdrant (qdrant/qdrant)
    8. qdrant-client (qdrant/qdrant-client)
    9. Weaviate (weaviate/weaviate)
    10. weaviate-client (weaviate/weaviate-python-client)
    11. Faiss (facebookresearch/faiss)

    AI recommended 11 alternatives but never named timescale/pgai. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How to build AI applications and enable natural language to SQL with PostgreSQL?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. OpenAI API
    3. GPT-4
    4. GPT-3.5 Turbo
    5. Anthropic's Claude
    6. Llama 2
    7. SQLAlchemy
    8. PostgreSQL
    9. FastAPI
    10. Pgvector

    AI recommended 10 alternatives but never named timescale/pgai. 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 timescale/pgai?
    pass
    AI named timescale/pgai explicitly

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

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

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

Embed your GEO score

Drop this badge into the README of timescale/pgai. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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timescale/pgai — 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