RRepoGEO

REPOGEO REPORT · LITE

adithya-s-k/omniparse

Default branch main · commit 9d1ae83c · scanned 5/16/2026, 3:47:39 PM

GitHub: 6,818 stars · 541 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 adithya-s-k/omniparse, 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
    Strengthen README opening to explicitly position as GenAI data platform

    Why:

    CURRENT
    > [!IMPORTANT]
>
>OmniParse is a platform that ingests and parses any unstructured data into structured, actionable data optimized for GenAI (LLM) applications. Whether you are working with documents, tables, images, videos, audio files, or web pages, OmniParse prepares your data to be clean, structured, and ready for AI applications such as RAG, fine-tuning, and more
    COPY-PASTE FIX
    > [!IMPORTANT]
>
>OmniParse is an open-source data preparation platform and toolkit designed to ingest and parse any unstructured data into structured, actionable data optimized for GenAI (LLM) applications like RAG and fine-tuning. It handles diverse data formats—documents, tables, images, videos, audio files, and web pages—preparing your data to be clean, structured, and ready for AI applications.
  • hightopics#2
    Add category-defining topics for GenAI data preparation

    Why:

    CURRENT
    ingestion-api, ocr, omniparser, parse-server, parser-library, vision-transformer, web-crawler, whisper-api
    COPY-PASTE FIX
    ingestion-api, ocr, omniparser, parse-server, parser-library, vision-transformer, web-crawler, whisper-api, llm-applications, rag, data-preparation, ai-framework, unstructured-data, multimodal-ai
  • mediumcomparison#3
    Add a 'Comparison with Alternatives' section to the README

    Why:

    COPY-PASTE FIX
    ## Comparison with Alternatives

OmniParse differentiates itself with an LLM-powered, schema-driven approach to universally parse and structure data from a wide variety of input formats (including unstructured and semi-structured data) into a consistent JSON output. Unlike general-purpose parsing libraries, OmniParse is specifically optimized for GenAI applications, providing a comprehensive, local-first solution for multimodal data preparation. While tools like LangChain and LlamaIndex focus on orchestration, OmniParse excels as the foundational data ingestion and structuring layer.

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 adithya-s-k/omniparse
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 1×
  2. LlamaIndex · recommended 1×
  3. Unstructured.io · recommended 1×
  4. Apache NiFi · recommended 1×
  5. Airbyte · recommended 1×
  • CATEGORY QUERY
    Need a tool to ingest and structure diverse unstructured data for large language model applications.
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Unstructured.io
    4. Apache NiFi
    5. Airbyte
    6. Haystack

    AI recommended 6 alternatives but never named adithya-s-k/omniparse. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are good open-source libraries for extracting structured data from documents, videos, and web pages locally?
    you: not recommended
    AI recommended (in order):
    1. Playwright (microsoft/playwright)
    2. Beautiful Soup (crummy/BeautifulSoup)
    3. Apache Tika (apache/tika)
    4. pdfminer.six (pdfminer/pdfminer.six)
    5. OpenCV (opencv/opencv)
    6. Pytesseract (madmaze/pytesseract)
    7. spaCy (explosion/spaCy)

    AI recommended 7 alternatives but never named adithya-s-k/omniparse. 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 adithya-s-k/omniparse?
    pass
    AI named adithya-s-k/omniparse explicitly

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

  • If a team adopts adithya-s-k/omniparse in production, what risks or prerequisites should they evaluate first?
    pass
    AI named adithya-s-k/omniparse 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 adithya-s-k/omniparse solve, and who is the primary audience?
    pass
    AI named adithya-s-k/omniparse 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 adithya-s-k/omniparse. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/adithya-s-k/omniparse.svg)](https://repogeo.com/en/r/adithya-s-k/omniparse)
HTML
<a href="https://repogeo.com/en/r/adithya-s-k/omniparse"><img src="https://repogeo.com/badge/adithya-s-k/omniparse.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

adithya-s-k/omniparse — 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