RRepoGEO

REPOGEO REPORT · LITE

QQ3221197721/cloudai-fusion

Default branch main · commit 89189a25 · scanned 6/1/2026, 10:27:02 PM

GitHub: 717 stars · 40 forks

AI VISIBILITY SCORE
30 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 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 QQ3221197721/cloudai-fusion, 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

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highabout#1
    Add a concise description to the About section

    Why:

    COPY-PASTE FIX
    Unified cloud-native AI management platform for multi-cloud Kubernetes, optimizing GPU scheduling and operations with AI agents.
  • mediumreadme#2
    Clarify the license terms in the README

    Why:

    COPY-PASTE FIX
    Add a section or sentence in the README, for example: '## License
This project is licensed under the terms specified in the [LICENSE](LICENSE) file. Please refer to the file for full details on usage and distribution.'

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 QQ3221197721/cloudai-fusion
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Red Hat OpenShift AI
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Red Hat OpenShift AI · recommended 2×
  2. Kubeflow · recommended 2×
  3. Google Anthos · recommended 1×
  4. Google Cloud's AI Platform services · recommended 1×
  5. Vertex AI · recommended 1×
  • CATEGORY QUERY
    How to unify management of AI workloads and Kubernetes clusters across multiple cloud providers?
    you: not recommended
    AI recommended (in order):
    1. Google Anthos
    2. Google Cloud's AI Platform services
    3. Vertex AI
    4. Red Hat OpenShift
    5. OpenShift Platform Plus
    6. Red Hat OpenShift AI
    7. Open Data Hub
    8. Azure Arc
    9. Azure Machine Learning services
    10. Rancher by SUSE
    11. Kubeflow
    12. MLflow
    13. VMware Tanzu
    14. Tanzu Mission Control

    AI recommended 14 alternatives but never named QQ3221197721/cloudai-fusion. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What platform helps optimize GPU resource scheduling for cloud-native AI applications?
    you: not recommended
    AI recommended (in order):
    1. Kubeflow
    2. Run:ai
    3. Volcano
    4. NVIDIA GPU Operator
    5. Red Hat OpenShift AI
    6. Google Kubernetes Engine (GKE)
    7. Amazon Elastic Kubernetes Service (EKS)
    8. Karpenter

    AI recommended 8 alternatives but never named QQ3221197721/cloudai-fusion. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    fail

    Suggestion:

  • 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 QQ3221197721/cloudai-fusion?
    pass
    AI named QQ3221197721/cloudai-fusion explicitly

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

  • If a team adopts QQ3221197721/cloudai-fusion in production, what risks or prerequisites should they evaluate first?
    pass
    AI named QQ3221197721/cloudai-fusion 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 QQ3221197721/cloudai-fusion solve, and who is the primary audience?
    pass
    AI named QQ3221197721/cloudai-fusion 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 QQ3221197721/cloudai-fusion. 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/QQ3221197721/cloudai-fusion.svg)](https://repogeo.com/en/r/QQ3221197721/cloudai-fusion)
HTML
<a href="https://repogeo.com/en/r/QQ3221197721/cloudai-fusion"><img src="https://repogeo.com/badge/QQ3221197721/cloudai-fusion.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

QQ3221197721/cloudai-fusion — 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
QQ3221197721/cloudai-fusion — RepoGEO report