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Labelbox
Labeling · 1.1M monthly visits

Labelbox is a comprehensive data-centric AI platform, or "Data Factory," designed for AI teams. It provides integrated software, expert services, and a talent marketplace to create, manage, and evaluate high-quality training data for advanced AI models, including LLMs and multimodal systems.

VS
Prodigy
Annotation · 44.4K monthly visits

Prodigy is a scriptable annotation tool for AI, Machine Learning, and NLP, designed for developers. It enables rapid creation of high-quality training and evaluation data through model-assisted, human-in-the-loop workflows. It runs on your own infrastructure, ensuring complete data privacy and control.

Labelbox vs Prodigy: pricing, features, traffic, and use cases

Compare Labelbox and Prodigy across positioning, pricing, traffic, and user feedback using structured factual data.

Updated Aug 21, 2026

Product overview

Labelbox Product overview

Labelbox is a comprehensive data-centric AI platform, or "Data Factory," designed for AI teams. It provides integrated software, expert services, and a talent marketplace to create, manage, and evaluate high-quality training data for advanced AI models, including LLMs and multimodal systems.

Preview

Prodigy Product overview

Prodigy is a scriptable annotation tool for AI, Machine Learning, and NLP, designed for developers. It enables rapid creation of high-quality training and evaluation data through model-assisted, human-in-the-loop workflows. It runs on your own infrastructure, ensuring complete data privacy and control.

Preview

Detailed feature comparison

FeatureLabelboxProdigy
Primary categoryLabelingAnnotation
Added2025-08-112025-09-12
PricingFreemiumPaid
Official websitelabelbox.comprodi.gy
Product typeWebsiteWebsite
Performance data
User ratingNot verifiedNot verified
Comments00
Monthly visits1.1M44.4K
Monthly growth19.3%1.1%
Favorites94119
DetailsView detailsView details

Labelbox vs Prodigy monthly traffic

Compare Labelbox and Prodigy by monthly reach, traffic trend, visit depth, top regions, and acquisition sources.

How to interpret the traffic data

In the Labelbox vs Prodigy monthly traffic comparison, Labelbox currently shows 1.1M visits and Prodigy shows 44.4K; Labelbox has about 24.7 times the visible traffic of Prodigy, an absolute difference of about 1.1M visits. This reflects visible reach, not feature quality or paid users.

Both tools provide verified traffic details, so monthly trends, visit depth, regions, and acquisition sources can be compared on the same basis.

Labelbox monthly traffic:

Latest traffic

Monthly visits
1.1M
Avg. visit duration
4:51
Pages per visit
7.12
Bounce rate
29.75%
Data updated 2026-06-15

Monthly traffic trend

  • 2025/9: 1M Monthly visits
  • 2026/1: 1.1M Monthly visits
  • 2026/2: 1.1M Monthly visits
  • 2026/3: 848.5K Monthly visits
  • 2026/4: 918.3K Monthly visits
  • 2026/5: 1.1M Monthly visits

Top regions

Top 5 countries/regions
Country/regionPercentageTraffic
🇺🇸United States51.51%564.1K
🇮🇳India16.98%185.9K
🇫🇷France13.54%148.3K
🇲🇽Mexico10.56%115.6K
🇪🇬Egypt7.41%81.1K

Traffic sources

Source typePercentageTraffic
Direct60.34%660.7K
Referral29.82%326.5K
Email9.84%107.8K

Search keywords

alignerralignerr loginlabel boxlabelboxlabelbox login

Prodigy monthly traffic:

Latest traffic

Monthly visits
44.4K
Avg. visit duration
0:16
Pages per visit
1.79
Bounce rate
37.48%
Data updated 2026-06-15

Monthly traffic trend

  • 2025/9: 62K Monthly visits
  • 2026/1: 53.8K Monthly visits
  • 2026/2: 48.4K Monthly visits
  • 2026/3: 50.5K Monthly visits
  • 2026/4: 43.9K Monthly visits
  • 2026/5: 44.4K Monthly visits

Top regions

Top 5 countries/regions
Country/regionPercentageTraffic
🇺🇸United States50.4%22.4K
🇮🇳India16.77%7.4K
🇻🇳Vietnam11.88%5.3K
🇨🇦Canada11%4.9K
🇩🇪Germany9.95%4.4K

Search keywords

ner model for us addressprodigyprodigy softwareprodigy sshprodygy
Traffic-based selection guidance: If public market visibility is an important first-pass criterion, investigate Labelbox first. The final choice should still follow taxonomy, use case, and a real trial because higher traffic does not prove broader capabilities or better workflow fit.

Usage comparison

Compare the core capabilities of Labelbox and Prodigy

Labelbox Core features

Machine Learning
Labeling
Workflow Management

Prodigy Core features

Machine Learning
Annotation
Automation

Use cases

Labelbox Use cases

AI training
computer vision
data annotation
data labeling
human-in-the-loop
machine learning
NLP
llm
model evaluation
multimodal AI
reinforcement learning

Prodigy Use cases

AI training
computer vision
data annotation
data labeling
human-in-the-loop
machine learning
NLP
active learning
developer tool
natural language processing
python
spacy

Best suited roles

Labelbox Best suited roles

No verified data available

Prodigy Best suited roles

AI Researcher
Data Analyst
Data Scientist
Machine Learning Engineer
NLP Engineer
Software Developer

Labelbox vs Prodigy:In-depth comparison and selection guidance

First decide whether the products solve the same kind of need

This in-depth Labelbox vs Prodigy comparison uses only the product records, taxonomy, audience, traffic, and community signals available on this page. Labelbox is primarily listed under “Labeling”, while Prodigy is primarily listed under “Annotation”, so the first decision is whether your actual task matches their recorded scope.

The structured fields currently show these decision-relevant differences: Primary category (Labelbox: Labeling; Prodigy: Annotation); Pricing (Labelbox: Freemium; Prodigy: Paid); Monthly visits (Labelbox: 1.1M; Prodigy: 44.4K); Monthly growth (Labelbox: 19.3%; Prodigy: 1.1%); Favorites (Labelbox: 94; Prodigy: 119). These facts are more useful for selection than brand visibility alone.

What market visibility and monthly traffic mean

In the Labelbox vs Prodigy monthly traffic comparison, Labelbox currently shows 1.1M visits and Prodigy shows 44.4K; Labelbox has about 24.7 times the visible traffic of Prodigy, an absolute difference of about 1.1M visits. This reflects visible reach, not feature quality or paid users.

Both tools provide verified traffic details, so monthly trends, visit depth, regions, and acquisition sources can be compared on the same basis.

If public market visibility is an important first-pass criterion, investigate Labelbox first. The final choice should still follow taxonomy, use case, and a real trial because higher traffic does not prove broader capabilities or better workflow fit.

Product positioning, use cases, and roles

Labelbox and Prodigy currently overlap in shared categories: Machine Learning; shared tags: AI training, computer vision, data annotation, data labeling, human-in-the-loop, machine learning, and NLP. This can place both on the same shortlist, but it does not prove equal implementation, depth, or cost.

Labelbox's unique categories/tags are Labeling, Workflow Management, llm, model evaluation, multimodal AI, and reinforcement learning; Prodigy's are Annotation, Automation, active learning, developer tool, natural language processing, python, and spacy. These unique fields are the strongest differentiators: validate the product whose recorded scope matches the task instead of following traffic alone.

What ratings, comments, and favorites can tell you

Labelbox has no verified rating, 0 comments, 94 favorites, and 100 likes;Prodigy has no verified rating, 0 comments, 119 favorites, and 121 likes。

Neither product has enough rating or comment samples for a credible reputation ranking.

Selection guidance by actual need

When to evaluate Labelbox first

Put Labelbox on the priority trial list when the task aligns with “Labeling” and especially Labeling, Workflow Management, llm, model evaluation, multimodal AI, and reinforcement learning. This follows recorded positioning and does not imply unlisted capabilities are absent.

Labelbox also currently records: pricing is freemium, product type is website, 1.1M verified monthly visits, no verified user rating. Verify any hard requirement around price, platform, or reach before trial, and do not let sparse review data substitute for testing.

When to evaluate Prodigy first

Put Prodigy on the priority trial list when the task aligns with “Annotation” and especially Annotation, Automation, active learning, developer tool, natural language processing, and python, or the users include AI Researcher, Data Analyst, Data Scientist, and Machine Learning Engineer. This follows recorded positioning and does not imply unlisted capabilities are absent.

Prodigy also currently records: pricing is paid, product type is website, 44.4K verified monthly visits, no verified user rating. Verify any hard requirement around price, platform, or reach before trial, and do not let sparse review data substitute for testing.

How to validate the recommendation before deciding

The available data describes positioning, public visibility, and community signals, but it cannot prove output quality, speed, integration effort, privacy, or long-term cost in your workflow. Before deciding, run the same representative tasks in Labelbox and Prodigy, then record completion time, accuracy, manual corrections, and the real paid threshold. A like-for-like trial turns this comparison into a defensible adoption decision.

Comparison FAQ

How should I choose between Labelbox and Prodigy?
Compare positioning, pricing, taxonomy, and traffic maturity, then verify the latest details on each official website.
Where does this comparison data come from?
The factual baseline is derived from product, taxonomy, traffic, and community data. Reviewed editorial conclusions show their source and verification date.
What do unknown fields mean?
Unknown means there is not enough reliable evidence; the page does not fill gaps with assumptions.

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