RRepoGEO

REPOGEO REPORT · LITE

datalab-to/lift

Default branch master · commit 4ff031b8 · scanned 6/28/2026, 12:06:43 AM

GitHub: 587 stars · 55 forks

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 datalab-to/lift, 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 `lift`'s core purpose in the README's opening

    Why:

    CURRENT
    lift extracts structured JSON from PDFs and images by passing a schema. It's a 9B vision model that returns a JSON object matching your schema, with schema-constrained decoding guaranteeing valid output.
    COPY-PASTE FIX
    lift is a powerful document intelligence tool designed to extract structured JSON from PDFs and images by passing a schema. It leverages a 9B vision model to return a JSON object matching your schema, with schema-constrained decoding guaranteeing valid output.
  • mediumreadme#2
    Add a comparison or differentiation section to the README

    Why:

    COPY-PASTE FIX
    Add a new section, e.g., '## Why Choose lift?' or '## lift vs. Alternatives', detailing its unique advantages like schema-constrained decoding, 9B vision model, multi-page handling, and local/remote inference options, especially compared to traditional OCR or rule-based extractors.
  • lowtopics#3
    Add more specific topics

    Why:

    CURRENT
    ai, extract, ocr, pdf, python
    COPY-PASTE FIX
    ai, extract, ocr, pdf, python, document-intelligence, structured-data, json-extraction, large-language-models, vision-models

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 datalab-to/lift
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Adobe Acrobat Services API (PDF Extract API)
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Adobe Acrobat Services API (PDF Extract API) · recommended 1×
  2. layout-parser/layout-parser · recommended 1×
  3. camelot-dev/camelot · recommended 1×
  4. pymupdf/PyMuPDF · recommended 1×
  5. pdfminer/pdfminer.six · recommended 1×
  • CATEGORY QUERY
    How can I programmatically extract structured data from PDF files into JSON?
    you: not recommended
    AI recommended (in order):
    1. Adobe Acrobat Services API (PDF Extract API)
    2. LayoutParser (layout-parser/layout-parser)
    3. Camelot (camelot-dev/camelot)
    4. PyMuPDF (Fitz) (pymupdf/PyMuPDF)
    5. pdfminer.six (pdfminer/pdfminer.six)
    6. Tabula-py (tabulapdf/tabula-py)
    7. Docparser

    AI recommended 7 alternatives but never named datalab-to/lift. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for an AI tool to accurately extract schema-constrained JSON from document images.
    you: not recommended
    AI recommended (in order):
    1. Google Cloud Document AI
    2. Azure Form Recognizer
    3. Amazon Textract
    4. Rossum
    5. Nanonets
    6. Kofax RPA

    AI recommended 6 alternatives but never named datalab-to/lift. 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 datalab-to/lift?
    pass
    AI named datalab-to/lift explicitly

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

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

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

Embed your GEO score

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MARKDOWN (README)
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datalab-to/lift — 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