RRepoGEO

REPOGEO REPORT · LITE

plexe-ai/plexe

Default branch main · commit a1e05f6d · scanned 5/9/2026, 11:06:32 PM

GitHub: 2,567 stars · 254 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 plexe-ai/plexe, 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 H1 to specify its open-source, framework nature

    Why:

    CURRENT
    # plexe ✨

Build machine learning models using natural language.
    COPY-PASTE FIX
    # plexe ✨

An open-source, agentic framework to build machine learning models from natural language descriptions.
  • mediumabout#2
    Expand the 'About' description to highlight its framework nature

    Why:

    CURRENT
    ✨ Build a machine learning model from a prompt
    COPY-PASTE FIX
    ✨ An open-source, agentic framework to build machine learning models from natural language prompts and datasets.
  • mediumtopics#3
    Add more specific topics related to AutoML and low-code ML

    Why:

    CURRENT
    agentic-ai, agents, ai, machine-learning, ml, mlengineering, mlops, multiagent
    COPY-PASTE FIX
    agentic-ai, agents, ai, machine-learning, ml, mlengineering, mlops, multiagent, automl, low-code-ml, prompt-engineering, ml-automation

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 plexe-ai/plexe
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
H2O.ai Driverless AI
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. H2O.ai Driverless AI · recommended 2×
  2. DataRobot · recommended 2×
  3. Google Cloud AutoML Tables · recommended 1×
  4. Vertex AI Tabular Workflows · recommended 1×
  5. Microsoft Azure Machine Learning Designer · recommended 1×
  • CATEGORY QUERY
    How to build machine learning models using natural language descriptions and a dataset?
    you: not recommended
    AI recommended (in order):
    1. Google Cloud AutoML Tables
    2. Vertex AI Tabular Workflows
    3. Microsoft Azure Machine Learning Designer
    4. H2O.ai Driverless AI
    5. DataRobot
    6. Ludwig (uber/ludwig)
    7. Gradio (gradio-app/gradio)
    8. Hugging Face Transformers (huggingface/transformers)
    9. Python
    10. scikit-learn (scikit-learn/scikit-learn)
    11. NLTK (nltk/nltk)
    12. spaCy (explosion/spaCy)

    AI recommended 12 alternatives but never named plexe-ai/plexe. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools automate ML model creation from high-level problem descriptions?
    you: not recommended
    AI recommended (in order):
    1. Google Cloud AutoML
    2. H2O.ai Driverless AI
    3. DataRobot
    4. Microsoft Azure Machine Learning
    5. Amazon SageMaker Autopilot
    6. TPOT
    7. AutoGluon

    AI recommended 7 alternatives but never named plexe-ai/plexe. 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 plexe-ai/plexe?
    pass
    AI named plexe-ai/plexe explicitly

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

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

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MARKDOWN (README)
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HTML
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plexe-ai/plexe — 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