RRepoGEO

REPOGEO REPORT · LITE

PaddlePaddle/PaddleX

Default branch release/3.7 · commit ffb64904 · scanned 6/30/2026, 6:46:46 AM

GitHub: 6,174 stars · 1,203 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
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 PaddlePaddle/PaddleX, 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 the README introduction to emphasize 'open-source, low-code platform'

    Why:

    CURRENT
    PaddleX 3.0 是基于飞桨框架构建的低代码开发工具，它集成了众多开箱即用的预训练模型，可以实现模型从训练到推理的全流程开发，支持国内外多款主流硬件，助力AI 开发者进行产业实践。
    COPY-PASTE FIX
    PaddleX 3.0 is an open-source, low-code development platform built on the PaddlePaddle framework, designed for end-to-end industrial computer vision applications. It integrates numerous ready-to-use pre-trained models, enabling full-process development from training to inference, and supports multiple mainstream hardware platforms to empower AI developers in industrial practice.
  • mediumabout#2
    Update the 'About' description to be more specific about its nature

    Why:

    CURRENT
    All-in-One Development Tool based on PaddlePaddle
    COPY-PASTE FIX
    An open-source, low-code platform for end-to-end industrial computer vision development and deployment, powered by PaddlePaddle.
  • lowtopics#3
    Add 'low-code-ai' to the repository topics

    Why:

    CURRENT
    ai-pipelines, classification, deployment, formula-recognition, layout-detection, object-detection, ocr, pdf2markdown, pp-chatocr, segmentation, speech-recognition, time-series
    COPY-PASTE FIX
    ai-pipelines, classification, deployment, formula-recognition, layout-detection, low-code-ai, object-detection, ocr, pdf2markdown, pp-chatocr, segmentation, speech-recognition, time-series

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 PaddlePaddle/PaddleX
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Google Cloud Vertex AI Workbench
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Google Cloud Vertex AI Workbench · recommended 1×
  2. AutoML Vision · recommended 1×
  3. Document AI · recommended 1×
  4. Microsoft Azure Machine Learning · recommended 1×
  5. Azure Cognitive Services · recommended 1×
  • CATEGORY QUERY
    What low-code AI development platforms support various tasks like object detection and OCR?
    you: not recommended
    AI recommended (in order):
    1. Google Cloud Vertex AI Workbench
    2. AutoML Vision
    3. Document AI
    4. Microsoft Azure Machine Learning
    5. Azure Cognitive Services
    6. Azure Computer Vision
    7. Azure Form Recognizer
    8. Amazon SageMaker Canvas
    9. Amazon Rekognition
    10. Amazon Textract
    11. DataRobot
    12. H2O.ai H2O Driverless AI

    AI recommended 12 alternatives but never named PaddlePaddle/PaddleX. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a comprehensive toolkit for training and deploying AI models across diverse hardware platforms.
    you: not recommended
    AI recommended (in order):
    1. TensorFlow
    2. PyTorch
    3. ONNX (Open Neural Network Exchange)
    4. NVIDIA TensorRT
    5. OpenVINO Toolkit
    6. MLflow

    AI recommended 6 alternatives but never named PaddlePaddle/PaddleX. 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 PaddlePaddle/PaddleX?
    pass
    AI named PaddlePaddle/PaddleX explicitly

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

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

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

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