RRepoGEO

REPOGEO REPORT · LITE

Zipstack/unstract

Default branch main · commit 0538fdcc · scanned 5/11/2026, 6:36:26 AM

GitHub: 6,565 stars · 625 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 Zipstack/unstract, 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 H2 to emphasize open-source, LLM-driven IDP platform

    Why:

    CURRENT
    <h2>Turn Unstructured Documents into Structured Data</h2>
    COPY-PASTE FIX
    <h2>Open-Source LLM Platform for Structured Data Extraction from Unstructured Documents</h2>
  • highreadme#2
    Add a 'Why Unstract vs. LLM Frameworks?' section to the README

    Why:

    COPY-PASTE FIX
    ## Why Unstract vs. LLM Frameworks (LangChain, LlamaIndex)?

While tools like LangChain and LlamaIndex provide powerful components for building LLM applications, Unstract is a complete, deployable platform designed specifically for production-grade unstructured data extraction in API and ETL workflows. It offers built-in document processing, data validation, and deployment capabilities, abstracting away much of the infrastructure needed to go from raw document to structured JSON at scale.
  • mediumtopics#3
    Add 'intelligent-document-processing' and 'data-extraction-platform' to topics

    Why:

    CURRENT
    api-deployments, data-extraction, document-processing, etl-pipelines, open-source-data-pipeline, unstructured-data-extraction
    COPY-PASTE FIX
    api-deployments, data-extraction, document-processing, etl-pipelines, open-source-data-pipeline, unstructured-data-extraction, intelligent-document-processing, data-extraction-platform

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 Zipstack/unstract
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Google Cloud Document AI
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Google Cloud Document AI · recommended 1×
  2. Amazon Textract · recommended 1×
  3. Microsoft Azure Form Recognizer · recommended 1×
  4. UiPath Document Understanding · recommended 1×
  5. Rossum · recommended 1×
  • CATEGORY QUERY
    How to convert unstructured documents like PDFs into structured data using AI?
    you: not recommended
    AI recommended (in order):
    1. Google Cloud Document AI
    2. Amazon Textract
    3. Microsoft Azure Form Recognizer
    4. UiPath Document Understanding
    5. Rossum
    6. Kofax Intelligent Automation Platform
    7. Apache Tika
    8. Tesseract OCR
    9. OpenCV
    10. spaCy
    11. NLTK

    AI recommended 11 alternatives but never named Zipstack/unstract. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are good open-source tools for LLM-driven data extraction in ETL pipelines?
    you: not recommended
    AI recommended (in order):
    1. LangChain (langchain-ai/langchain)
    2. LlamaIndex (run-llama/llama_index)
    3. Haystack (deepset-ai/haystack)
    4. OpenAI Functions (openai/openai-python)
    5. Instructor (jxnl/instructor)
    6. Spacy (explosion/spaCy)
    7. Transformers (huggingface/transformers)

    AI recommended 7 alternatives but never named Zipstack/unstract. 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 Zipstack/unstract?
    pass
    AI named Zipstack/unstract explicitly

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

  • If a team adopts Zipstack/unstract in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Zipstack/unstract 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 Zipstack/unstract solve, and who is the primary audience?
    pass
    AI named Zipstack/unstract 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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  • Brand-free category queries5 vs 2 in Lite
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