RRepoGEO

REPOGEO REPORT · LITE

impira/docquery

Default branch main · commit 3744f08a · scanned 5/18/2026, 1:12:56 PM

GitHub: 1,779 stars · 134 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
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 impira/docquery, 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 relevant topics to the repository

    Why:

    COPY-PASTE FIX
    document-ai, llm, information-extraction, pdf-processing, ocr, python-library, natural-language-processing, question-answering
  • highreadme#2
    Refine the README's opening paragraph for clearer positioning

    Why:

    CURRENT
    DocQuery is a library and command-line tool that makes it easy to analyze semi-structured and unstructured documents (PDFs, scanned images, etc.) using large language models (LLMs). You simply point DocQuery at one or more documents and specify a question you want to ask. DocQuery is created by the team at Impira.
    COPY-PASTE FIX
    DocQuery is an open-source Python library and command-line tool designed for **local, programmatic information extraction and question answering from semi-structured and unstructured documents (PDFs, scanned images, etc.) using large language models (LLMs)**. It offers a self-contained solution for developers and data scientists to analyze documents by simply pointing it at files and specifying a natural language question, providing an alternative to cloud-based document AI services.
  • mediumhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://github.com/impira/docquery

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 impira/docquery
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Azure AI Document Intelligence
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Azure AI Document Intelligence · recommended 1×
  2. Google Cloud Document AI · recommended 1×
  3. AWS Textract · recommended 1×
  4. OpenAI GPT-4V (Vision) or GPT-4o · recommended 1×
  5. PaddleOCR · recommended 1×
  • CATEGORY QUERY
    How to extract specific information from PDFs and scanned images using an LLM?
    you: not recommended
    AI recommended (in order):
    1. Azure AI Document Intelligence
    2. Google Cloud Document AI
    3. AWS Textract
    4. OpenAI GPT-4V (Vision) or GPT-4o
    5. PaddleOCR
    6. Tesseract OCR
    7. Nanonets

    AI recommended 7 alternatives but never named impira/docquery. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What's a good Python library for programmatic document analysis and question answering?
    you: not recommended
    AI recommended (in order):
    1. Haystack
    2. LlamaIndex
    3. LangChain
    4. spaCy
    5. Hugging Face Transformers
    6. NLTK

    AI recommended 6 alternatives but never named impira/docquery. 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 impira/docquery?
    pass
    AI named impira/docquery explicitly

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

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

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

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impira/docquery — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite