REPOGEO REPORT · LITE

clearml/clearml

Default branch master · commit 00d35dd7 · scanned 5/20/2026, 2:37:11 PM

GitHub: 6,690 stars · 777 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 clearml/clearml, 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's main heading to clearly state its category

Why:

CURRENT

**ClearML - Auto-Magical Suite of tools to streamline your AI workflow </br>Experiment Manager, MLOps/LLMops and Data-Management**

COPY-PASTE FIX

**ClearML is a unified, end-to-end, open-source MLOps/LLMops platform for experiment tracking, data versioning, model management, pipeline orchestration, and remote execution.**

mediumcomparison#2

Add a comparison section or link to the README

Why:

COPY-PASTE FIX

Add a new section to the README, for example, `## ClearML vs. Alternatives`, with a sentence like: 'See how ClearML stands out from other MLOps platforms like MLflow, Kubeflow, and DVC in our detailed [comparison guide](https://clear.ml/docs/comparison).' (Adjust URL as needed).

lowtopics#3

Add 'llmops' to the repository topics

Why:

CURRENT

ai, clearml, control, deep-learning, deeplearning, devops, experiment, experiment-manager, k8s, machine-learning, machinelearning, mlops, trains, trainsai, version, version-control

COPY-PASTE FIX

ai, clearml, control, deep-learning, deeplearning, devops, experiment, experiment-manager, k8s, llmops, machine-learning, machinelearning, mlops, trains, trainsai, version, version-control

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 clearml/clearml

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

mlflow/mlflow

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

mlflow/mlflow · recommended 1×
kubeflow/kubeflow · recommended 1×
iterative/dvc · recommended 1×
Weights & Biases · recommended 1×
Comet ML · recommended 1×

CATEGORY QUERY
What tools help manage machine learning experiments, track results, and automate MLOps pipelines?
you: not recommended
AI recommended (in order):
1. MLflow (mlflow/mlflow)
2. Kubeflow (kubeflow/kubeflow)
3. DVC (iterative/dvc)
4. Weights & Biases
5. Comet ML
6. Metaflow (Netflix/metaflow)
7. Azure Machine Learning
8. Google Cloud AI Platform
9. Amazon SageMaker
AI recommended 9 alternatives but never named clearml/clearml. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Seeking a platform for data version control and orchestrating AI workloads on cloud infrastructure.
you: not recommended
AI recommended (in order):
1. DVC
2. Kubeflow
3. MLflow
4. AWS Step Functions
5. Azure Data Factory
6. Google Cloud Composer
7. Apache Airflow
8. Pachyderm
9. LakeFS
10. Astronomer
11. Domino Data Lab
AI recommended 11 alternatives but never named clearml/clearml. 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 clearml/clearml?
pass
AI named clearml/clearml explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts clearml/clearml in production, what risks or prerequisites should they evaluate first?
pass
AI named clearml/clearml 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 clearml/clearml solve, and who is the primary audience?
pass
AI named clearml/clearml 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 clearml/clearml. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

Live preview

MARKDOWN (README)

[![RepoGEO](https://repogeo.com/badge/clearml/clearml.svg)](https://repogeo.com/en/r/clearml/clearml)

HTML

<a href="https://repogeo.com/en/r/clearml/clearml"><img src="https://repogeo.com/badge/clearml/clearml.svg" alt="RepoGEO" /></a>

Pro

Subscribe to Pro for deep diagnoses

clearml/clearml — 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