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Scale AI
Beschriftung · 624.7K monatliche besuche

Scale AI ist eine Full-Stack-Plattform, die die KI-Entwicklung durch die Bereitstellung hochwertiger Daten, Modellbewertung und Feinabstimmungsdienste beschleunigt. Sie richtet sich an führende KI-Labore, Unternehmen und Regierungsbehörden und bietet eine umfassende Daten-Engine für RLHF, Datenkennzeichnung und -generierung, um fortschrittliche generative KI und LLMs zu betreiben.

VS
SuperAnnotate
Beschriftung · 406.4K monatliche besuche

SuperAnnotate ist eine führende KI-Datenplattform, die die gesamte Datenpipeline für maschinelles Lernen optimiert. Sie ermöglicht es Teams, hochwertige multimodale Datensätze (Bild, Video, Text, Audio) zu annotieren, zu verwalten und zu kuratieren, um die Modellentwicklung zu beschleunigen, einschließlich komplexer Workflows wie RLHF, RAG und SFT. Sie wurde entwickelt, um die Modellgenauigkeit und -effizienz zu verbessern.

Scale AI vs SuperAnnotate: Preise, Funktionen und Traffic

Vergleiche Scale AI und SuperAnnotate nach Positionierung, Preis, Funktionen, Traffic und Nutzerfeedback.

Aktualisiert 05.08.2026

Produktübersicht

Scale AI Produktübersicht

Scale AI ist eine Full-Stack-Plattform, die die KI-Entwicklung durch die Bereitstellung hochwertiger Daten, Modellbewertung und Feinabstimmungsdienste beschleunigt. Sie richtet sich an führende KI-Labore, Unternehmen und Regierungsbehörden und bietet eine umfassende Daten-Engine für RLHF, Datenkennzeichnung und -generierung, um fortschrittliche generative KI und LLMs zu betreiben.

Preview

SuperAnnotate Produktübersicht

SuperAnnotate ist eine führende KI-Datenplattform, die die gesamte Datenpipeline für maschinelles Lernen optimiert. Sie ermöglicht es Teams, hochwertige multimodale Datensätze (Bild, Video, Text, Audio) zu annotieren, zu verwalten und zu kuratieren, um die Modellentwicklung zu beschleunigen, einschließlich komplexer Workflows wie RLHF, RAG und SFT. Sie wurde entwickelt, um die Modellgenauigkeit und -effizienz zu verbessern.

Preview

Detailed feature comparison

FeatureScale AISuperAnnotate
HauptkategorieBeschriftungBeschriftung
Hinzugefügt2025-08-102025-08-05
PreismodellKostenpflichtigFreemium
Offizielle Websitescale.comwww.superannotate.com
ProdukttypWebsiteWebsite
Performance data
NutzerbewertungNicht verifiziertNicht verifiziert
Kommentare00
Monatliche Besuche624.7K406.4K
Monatliches Wachstum-2.2%2.2%
Favoriten10789
DetailsDetails ansehenDetails ansehen

Scale AI vs SuperAnnotate monthly traffic

Compare Scale AI and SuperAnnotate by monthly reach, traffic trend, visit depth, top regions, and acquisition sources.

How to interpret the traffic data

In the Scale AI vs SuperAnnotate monthly traffic comparison, Scale AI currently shows 624.7K visits and SuperAnnotate shows 406.4K; Scale AI has about 1.5 times the visible traffic of SuperAnnotate, an absolute difference of about 218.3K 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.

Scale AI monthly traffic:

Latest traffic

Monatliche Besuche
624.7K
Ø Besuchsdauer
1:21
Seiten pro Besuch
2.49
Absprungrate
49.38%
Data updated 2026-06-15

Monthly traffic trend

  • 2025/9: 553.8K Monatliche Besuche
  • 2026/1: 699.1K Monatliche Besuche
  • 2026/2: 549.1K Monatliche Besuche
  • 2026/3: 590.2K Monatliche Besuche
  • 2026/4: 638.4K Monatliche Besuche
  • 2026/5: 624.7K Monatliche Besuche

Top-Regionen

Top 5 countries/regions
Country/regionPercentageTraffic
🇺🇸United States69.42%433.6K
🇮🇳India13.06%81.6K
🇬🇧United Kingdom6.45%40.3K
🇲🇽Mexico6.34%39.6K
🇨🇳China4.73%29.5K

Traffic-Quellen

Source typePercentageTraffic
Direkt82.65%516.3K
Verweis14.81%92.5K
E-Mail2.54%15.9K

Suchbegriffe

scalescale aiscaleaiscale ai careersswe-bench pro

SuperAnnotate monthly traffic:

Latest traffic

Monatliche Besuche
406.4K
Ø Besuchsdauer
4:18
Seiten pro Besuch
4.91
Absprungrate
34.06%
Data updated 2026-06-15

Monthly traffic trend

  • 2025/9: 234.7K Monatliche Besuche
  • 2026/1: 368.8K Monatliche Besuche
  • 2026/2: 400K Monatliche Besuche
  • 2026/3: 541K Monatliche Besuche
  • 2026/4: 397.6K Monatliche Besuche
  • 2026/5: 406.4K Monatliche Besuche

Top-Regionen

Top 5 countries/regions
Country/regionPercentageTraffic
🇺🇸United States64.07%260.4K
🇮🇳India20.8%84.5K
🇩🇪Germany6.28%25.5K
🇧🇩Bangladesh5.79%23.5K
🇮🇱Israel3.06%12.4K

Traffic-Quellen

Source typePercentageTraffic
Direkt83.64%339.9K
E-Mail8.59%34.9K
Verweis7.77%31.6K

Suchbegriffe

data annotationdataannotationdiffusion modelssuperannotatewhat is data annotation
Traffic-based selection guidance: If public market visibility is an important first-pass criterion, investigate Scale AI 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 Scale AI and SuperAnnotate

Scale AI Core features

Beschriftung
Plattform
Automatisierung

SuperAnnotate Core features

Beschriftung
MLOps
Workflow-Management

Use cases

Scale AI Use cases

Datenlabeling
Großes Sprachmodell
RLHF
KI-Plattform
KI-Sicherheit
Daten-Engine
Unternehmens-KI
Feinabstimmung
Generative KI
Modellbewertung

SuperAnnotate Use cases

Datenlabeling
Großes Sprachmodell
RLHF
KI-Datenplattform
KI-Trainingsdaten
Computer Vision
Datenannotation
Dataset-Management
Mensch-in-der-Schleife
MLOps
Retrieval-Augmentierte Generierung
SFT

Scale AI vs SuperAnnotate:In-depth comparison and selection guidance

First decide whether the products solve the same kind of need

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

The structured fields currently show these decision-relevant differences: Pricing (Scale AI: Paid; SuperAnnotate: Freemium); Monthly visits (Scale AI: 624.7K; SuperAnnotate: 406.4K); Monthly growth (Scale AI: -2.2%; SuperAnnotate: 2.2%); Favorites (Scale AI: 107; SuperAnnotate: 89); Website (Scale AI: scale.com; SuperAnnotate: www.superannotate.com). These facts are more useful for selection than brand visibility alone.

What market visibility and monthly traffic mean

In the Scale AI vs SuperAnnotate monthly traffic comparison, Scale AI currently shows 624.7K visits and SuperAnnotate shows 406.4K; Scale AI has about 1.5 times the visible traffic of SuperAnnotate, an absolute difference of about 218.3K 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 Scale AI 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

Scale AI and SuperAnnotate currently overlap in shared categories: Beschriftung; shared tags: Datenlabeling, Großes Sprachmodell und RLHF. This can place both on the same shortlist, but it does not prove equal implementation, depth, or cost.

Scale AI's unique categories/tags are Plattform, Automatisierung, KI-Plattform, KI-Sicherheit, Daten-Engine, Unternehmens-KI, Feinabstimmung und Generative KI; SuperAnnotate's are MLOps, Workflow-Management, KI-Datenplattform, KI-Trainingsdaten, Computer Vision, Datenannotation, Dataset-Management und Mensch-in-der-Schleife. 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

Scale AI has no verified rating, 0 comments, 107 favorites, and 110 likes;SuperAnnotate has no verified rating, 0 comments, 89 favorites, and 101 likes。

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

Selection guidance by actual need

When to evaluate Scale AI first

Put Scale AI on the priority trial list when the task aligns with “Beschriftung” and especially Plattform, Automatisierung, KI-Plattform, KI-Sicherheit, Daten-Engine und Unternehmens-KI. This follows recorded positioning and does not imply unlisted capabilities are absent.

Scale AI also currently records: pricing is paid, product type is website, 624.7K 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 SuperAnnotate first

Put SuperAnnotate on the priority trial list when the task aligns with “Beschriftung” and especially MLOps, Workflow-Management, KI-Datenplattform, KI-Trainingsdaten, Computer Vision und Datenannotation. This follows recorded positioning and does not imply unlisted capabilities are absent.

SuperAnnotate also currently records: pricing is freemium, product type is website, 406.4K 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 Scale AI and SuperAnnotate, 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.

Vergleichs-FAQ

How should I choose between Scale AI and SuperAnnotate?
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.