REPOGEO REPORT · LITE

HumanSignal/label-studio-ml-backend

Default branch master · commit 5b32433b · scanned 5/21/2026, 3:56:59 PM

GitHub: 1,045 stars · 470 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

22 /100

Critical

Category recall

0 / 2

Not recommended in any query

Rule findings

1 pass · 1 warn · 0 fail

Objective metadata checks

AI knows your name

1 / 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 HumanSignal/label-studio-ml-backend, 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

highreadme#1

Strengthen the README's opening sentence to emphasize its role in data labeling automation

Why:

CURRENT

# What is the Label Studio ML backend?

The Label Studio ML backend is an SDK that lets you wrap your machine learning code and turn it into a web server. The web server can be connected to a running Label Studio instance to automate labeling tasks.

COPY-PASTE FIX

# Label Studio ML Backend: Automate Data Labeling with Custom Machine Learning Models

The Label Studio ML Backend is the official SDK for integrating your machine learning code directly with Label Studio, transforming your models into a web server for automated data labeling, pre-annotation, and active learning workflows.

mediumhomepage#2
Add a homepage URL to the repository metadata
Why:
COPY-PASTE FIX
```
https://labelstud.io/
```

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 HumanSignal/label-studio-ml-backend

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

snorkel-team/snorkel

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

snorkel-team/snorkel · recommended 1×
heartexlabs/label-studio · recommended 1×
argilla-io/argilla · recommended 1×
Amazon SageMaker Ground Truth · recommended 1×
Google Cloud AI Platform Data Labeling · recommended 1×

CATEGORY QUERY
How to integrate custom machine learning models into a data labeling pipeline for automation?
you: not recommended
AI recommended (in order):
1. Snorkel (snorkel-team/snorkel)
2. Label Studio (heartexlabs/label-studio)
3. Argilla (argilla-io/argilla)
4. Amazon SageMaker Ground Truth
5. Google Cloud AI Platform Data Labeling
6. V7
AI recommended 6 alternatives but never named HumanSignal/label-studio-ml-backend. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Tool to serve machine learning models as an API for automated data annotation platforms?
you: not recommended
AI recommended (in order):
1. MLflow (mlflow/mlflow)
2. Seldon Core (SeldonIO/seldon-core)
3. KServe (kserve/kserve)
4. FastAPI (tiangolo/fastapi)
5. Triton Inference Server (triton-inference-server/server)
6. AWS SageMaker Endpoints
7. Google Cloud Vertex AI Endpoints
AI recommended 7 alternatives but never named HumanSignal/label-studio-ml-backend. This is the gap to close.
Show full AI answer

Objective checks

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

Metadata completeness
warn
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 HumanSignal/label-studio-ml-backend?
pass
AI did not name HumanSignal/label-studio-ml-backend — likely talking about a different project
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts HumanSignal/label-studio-ml-backend in production, what risks or prerequisites should they evaluate first?
pass
AI named HumanSignal/label-studio-ml-backend 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 HumanSignal/label-studio-ml-backend solve, and who is the primary audience?
pass
AI did not name HumanSignal/label-studio-ml-backend — likely talking about a different project
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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MARKDOWN (README)

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HumanSignal/label-studio-ml-backend — 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