# Scale vs SuperAnnotate

Scale enregistre 616 915 visites mensuelles avec une croissance mensuelle de +12,5 % et un modèle tarifaire Tarifs sur demande. SuperAnnotate enregistre 386 034 visites mensuelles avec une croissance de +37,4 % et un modèle tarifaire Essai gratuit, Tarifs sur demande.

| Métrique | [Scale](https://openaitools.app/fr/tool/scale) | [SuperAnnotate](https://openaitools.app/fr/tool/super-annotate) |
| :--- | :--- | :--- |
| URL du site web | https://scale.com | https://www.superannotate.com |
| Catégories | Outils de développement IA, Large Language Models (LLMs), Modèles IA, AI Agent | AI Workflow, Outils de développement IA, Gestion de projet IA |
| Modèle tarifaire | Tarifs sur demande | Essai gratuit, Tarifs sur demande |
| Visites mensuelles | 616 915 | 386 034 |
| Taux de croissance mensuel | +12,5 % | +37,4 % |
| Marché principal | États-Unis | États-Unis |
| Visites directes | 191 408 | 248 258 |
| Score d'avis | 4,7 | 4,6 |
| Nombre d'enregistrements | 3 | 0 |
| Plateformes prises en charge | Site web | Site web |

## Scale

Scale is an enterprise AI company that supplies the data, evaluation and deployment layers behind production AI. Its Data Engine sources and labels training data for frontier models, its evaluation work benchmarks model capability, and its platform teams help enterprises and governments move AI systems from pilot into real operations.

**Tarifs et offres:** Contact for pricing. Scale does not publish rates; engagements are scoped through a sales conversation and depend on data volume, services and programme complexity.

- **Data Engine:** Human-sourced and expert-annotated training data, including specialist contributors with advanced degrees, at the quality bar frontier labs require.
- **Model evaluation & benchmarks:** Public leaderboards plus private benchmarks that test model capability and safety for the most ambitious AI developers.
- **Enterprise AI applications:** Platform and services teams that pick the right use case, build the system and take ownership of the outcome.
- **Agentic deployment:** Agentic systems designed around measurable business outcomes across private equity portfolios, energy and healthcare operations.
- **Domain expertise:** Programmes spanning healthcare, robotics, defence, public sector and enterprise with human oversight built in.

**Forces:** Backed by a long track record in training data and model evaluation.; End-to-end coverage from data sourcing through to deployed systems.; Experienced with regulated, classified and safety-critical environments.; Benchmarks and leaderboards give an independent view of model capability.

**Limites:** No public pricing or self-serve signup - you need a sales conversation to get started.; Enterprise-scale contracting and data operations require real internal commitment.; Overkill for small teams with modest data or evaluation needs.; Some projects involve sensitive government and defence work with strict compliance overhead.

[Profile (Markdown)](https://openaitools.app/fr/tool/scale.md)

## SuperAnnotate

SuperAnnotate is an AI data platform that combines a collaborative multimodal annotation editor, an expert data-operations team, and the orchestration layer needed to move curated datasets into training, evaluation, and production pipelines. It is aimed at teams building computer vision, NLP, audio, and generative AI systems who need reliable, high-quality ground truth at scale.

**Tarifs et offres:** SuperAnnotate publishes three main tiers: Starter, Pro, and Enterprise. Starter is described as an entry point for small projects, Pro targets scaled AI and MLOps workloads and is sold via a demo request, and Enterprise is quoted through sales for well-established, recurring, high-volume programs. Published plan comparison highlights compute orchestration allowances of roughly 1K compute hours on Starter, 2.5K on Pro, and 10K on Enterprise, with SSO, dedicated Slack channels, a customer success manager, a solutions engineer, and AI DataOps consulting reserved for higher tiers. Exact prices are not listed publicly, so you should contact the vendor for a quote.

- **Customizable multimodal editor:** One configurable annotation surface for image, video, text, and audio projects, so multimodal datasets can be labeled without switching tools.
- **Data curation and exploration:** Search, filter, and inspect datasets to find the examples that will most improve a model, then route them into targeted annotation or review queues.
- **Analytics and insights:** Dashboards for annotation volume, reviewer agreement, and project progress, plus advanced analytics on upper tiers for program-level reporting.
- **Compute orchestration:** Metered orchestration capacity for running annotation, evaluation, and data-processing workloads, scaled by plan from roughly 1K to 10K compute hours.
- **Managed Data Operations:** Optional access to SuperAnnotate's own annotation experts and AI DataOps consultants to run large or specialized data programs end to end.

**Forces:** Unified editor removes the need to maintain separate tools per modality; Rich project management and quality analytics suited to large distributed teams; Enterprise-grade governance features such as SSO and dedicated support channels; Managed data-operations services let you outsource complex or high-volume programs

**Limites:** No public list price, so budgeting requires a sales conversation; Advanced analytics, SSO, and dedicated support are locked to higher tiers; The breadth of features can be heavy for individuals or very small teams; Compute orchestration capacity is metered and may require planning for large jobs

[Profile (Markdown)](https://openaitools.app/fr/tool/super-annotate.md)

## Questions fréquentes

### Comment Scale et SuperAnnotate se comparent-ils en termes de trafic mensuel ?

Scale enregistre 616 915 visites mensuelles, tandis que SuperAnnotate enregistre 386 034. Les estimations de trafic décrivent la taille de l'audience, pas la qualité du produit.

### Comment leurs taux de croissance se comparent-ils ?

Scale a un taux de croissance mensuel de +12,5 % ; SuperAnnotate a +37,4 %.

### Comment les tarifs se comparent-ils ?

Scale : Tarifs sur demande. Contact for pricing. Scale does not publish rates; engagements are scoped through a sales conversation and depend on data volume, services and programme complexity. SuperAnnotate : Essai gratuit, Tarifs sur demande. SuperAnnotate publishes three main tiers: Starter, Pro, and Enterprise. Starter is described as an entry point for small projects, Pro targets scaled AI and MLOps workloads and is sold via a demo request, and Enterprise is quoted through sales for well-established, recurring, high-volume programs. Published plan comparison highlights compute orchestration allowances of roughly 1K compute hours on Starter, 2.5K on Pro, and 10K on Enterprise, with SSO, dedicated Slack channels, a customer success manager, a solutions engineer, and AI DataOps consulting reserved for higher tiers. Exact prices are not listed publicly, so you should contact the vendor for a quote.

## Alternatives

| # | Nom de l'outil | Visites mensuelles | Taux de croissance mensuel | Modèle tarifaire | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [Roboflow](https://openaitools.app/fr/tool/roboflow) | 1 431 204 | +6,6 % | Freemium, Tarifs sur demande | Simplifie l'annotation des jeux de données de vision par ordinateur et l'entraînement de modèles, mais convient moins aux tâches textuelles générales par LLM. | [.md](https://openaitools.app/fr/tool/roboflow.md) |
| 2 | [Labelbox](https://openaitools.app/fr/tool/labelbox) | 762 803 | -22,8 % | Tarifs sur demande | Solide étiquetage de données d'entreprise et automatisation d'agents, mais avec une interface collaborative et une tarification distinctes. | [.md](https://openaitools.app/fr/tool/labelbox.md) |
| 3 | [Appen](https://openaitools.app/fr/tool/appen-com) | 665 840 | +0,2 % | Tarifs sur demande | Extensive human-validated training datasets and alignment services, but lacks SuperAnnotate's self-serve software platform flexibility. | [.md](https://openaitools.app/fr/tool/appen-com.md) |
| 4 | [Weights & Biases (CoreWeave Forge)](https://openaitools.app/fr/tool/prompts) | 315 624 | -80,2 % | Freemium, Tarifs sur demande, Gratuit | Exceptional for ML experiment tracking and LLM evaluation, but does not provide traditional computer vision data labeling environments. | [.md](https://openaitools.app/fr/tool/prompts.md) |
| 5 | [Arize AI](https://openaitools.app/fr/tool/arize-com) | 249 028 | +3,2 % | Payant, Tarifs sur demande | Focuses on post-deployment LLM observability and evaluation rather than training data generation or annotation. | [.md](https://openaitools.app/fr/tool/arize-com.md) |
| 6 | [Encord](https://openaitools.app/fr/tool/encord-com) | 244 204 | +9,4 % | Tarifs sur demande | Excellente infrastructure de données multimodales pour la vision par ordinateur, mais il lui manque certains outils de gestion de projets d'entreprise de SuperAnnotate. | [.md](https://openaitools.app/fr/tool/encord-com.md) |
| 7 | [Defined.ai](https://openaitools.app/fr/tool/definedcrowd-com) | 146 251 | -21 % | Tarifs sur demande | Strong enterprise data collection and annotation services, but focuses more on managed datasets than self-serve tooling. | [.md](https://openaitools.app/fr/tool/definedcrowd-com.md) |
| 8 | [Label Studio](https://openaitools.app/fr/tool/label-studio) | 137 199 | -16,1 % | Tarifs sur demande, Gratuit | Étiquetage de données open source puissant et hautement personnalisable, mais nécessite un auto-hébergement et manque de flux de travail d'entreprise gérés prêts à l'emploi. | [.md](https://openaitools.app/fr/tool/label-studio.md) |
| 9 | [Future AGI](https://openaitools.app/fr/tool/future-agi) | 121 741 | -7,8 % | Freemium, Usage-based | Construisez, simulez, évaluez et surveillez des agents IA qui s'améliorent seuls | [.md](https://openaitools.app/fr/tool/future-agi.md) |
| 10 | [Maxim AI](https://openaitools.app/fr/tool/maxim-ai) | 121 351 | +10 % | Contact for Pricing, Free Open Source | Provides LLM evaluation and testing workflows, but lacks Scale's massive human-in-the-loop data labeling services. | [.md](https://openaitools.app/fr/tool/maxim-ai.md) |

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Source : https://openaitools.app/fr/compare/scale-vs-super-annotate

More Markdown: [Catégories](https://openaitools.app/fr/categories.md) · [Classements de trafic](https://openaitools.app/fr/rankings.md) · [llms.txt](https://openaitools.app/fr/llms.txt)