# Scale vs SuperAnnotate

Scale는 월간 방문 616,915, 전월 대비 성장률 +12.5%, 가격 문의 가격 모델을 기록합니다. SuperAnnotate는 월간 방문 386,034, 성장률 +37.4%, 무료 체험, 가격 문의 가격 모델을 기록합니다.

| 지표 | [Scale](https://openaitools.app/ko/tool/scale) | [SuperAnnotate](https://openaitools.app/ko/tool/super-annotate) |
| :--- | :--- | :--- |
| 웹사이트 URL | https://scale.com | https://www.superannotate.com |
| 카테고리 | AI 개발자 도구, Large Language Models (LLMs), AI 모델, AI Agent | AI Workflow, AI 개발자 도구, AI 프로젝트 관리 |
| 가격 모델 | 가격 문의 | 무료 체험, 가격 문의 |
| 월간 방문 수 | 616,915 | 386,034 |
| 전월 대비 성장률 | +12.5% | +37.4% |
| 주요 시장 | 미국 | 미국 |
| 직접 방문 | 191,408 | 248,258 |
| 리뷰 점수 | 4.7 | 4.6 |
| 저장 수 | 3 | 0 |
| 지원 플랫폼 | 웹사이트 | 웹사이트 |

## 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.

**가격 및 요금제:** 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.

**강점:** 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.

**한계:** 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/ko/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.

**가격 및 요금제:** 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.

**강점:** 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

**한계:** 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/ko/tool/super-annotate.md)

## 자주 묻는 질문

### Scale과(와) SuperAnnotate의 월간 트래픽은 어떻게 비교되나요?

Scale의 월간 방문 수는 616,915이고, SuperAnnotate는 386,034입니다. 트래픽 추정치는 제품 품질이 아니라 사용자 규모를 나타냅니다.

### 두 도구의 성장률은 어떻게 비교되나요?

Scale의 전월 대비 성장률은 +12.5%이며, SuperAnnotate는 +37.4%입니다.

### 가격은 어떻게 비교되나요?

Scale: 가격 문의. 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: 무료 체험, 가격 문의. 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.

## 대안

| # | 도구 이름 | 월간 방문 수 | 전월 대비 성장률 | 가격 모델 | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [Roboflow](https://openaitools.app/ko/tool/roboflow) | 1,431,204 | +6.6% | 무료+유료, 가격 문의 | 컴퓨터 비전 데이터셋 어노테이션 및 모델 학습을 간소화하지만, 일반적인 LLM 텍스트 작업에는 덜 적합합니다. | [.md](https://openaitools.app/ko/tool/roboflow.md) |
| 2 | [Labelbox](https://openaitools.app/ko/tool/labelbox) | 762,803 | -22.8% | 가격 문의 | 강력한 엔터프라이즈 데이터 라벨링과 에이전트 자동화를 제공하지만, 협업 인터페이스와 가격 구조가 다릅니다. | [.md](https://openaitools.app/ko/tool/labelbox.md) |
| 3 | [Appen](https://openaitools.app/ko/tool/appen-com) | 665,840 | +0.2% | 가격 문의 | Extensive human-validated training datasets and alignment services, but lacks SuperAnnotate's self-serve software platform flexibility. | [.md](https://openaitools.app/ko/tool/appen-com.md) |
| 4 | [Weights & Biases(CoreWeave Forge)](https://openaitools.app/ko/tool/prompts) | 315,624 | -80.2% | 무료+유료, 가격 문의, 무료 | Exceptional for ML experiment tracking and LLM evaluation, but does not provide traditional computer vision data labeling environments. | [.md](https://openaitools.app/ko/tool/prompts.md) |
| 5 | [Arize AI](https://openaitools.app/ko/tool/arize-com) | 249,028 | +3.2% | 유료, 가격 문의 | Focuses on post-deployment LLM observability and evaluation rather than training data generation or annotation. | [.md](https://openaitools.app/ko/tool/arize-com.md) |
| 6 | [Encord](https://openaitools.app/ko/tool/encord-com) | 244,204 | +9.4% | 가격 문의 | 컴퓨터 비전을 위한 우수한 멀티모달 데이터 인프라를 갖추고 있으나, SuperAnnotate의 광범위한 엔터프라이즈 프로젝트 관리 도구 일부가 빠져 있습니다. | [.md](https://openaitools.app/ko/tool/encord-com.md) |
| 7 | [Defined.ai](https://openaitools.app/ko/tool/definedcrowd-com) | 146,251 | -21% | 가격 문의 | Strong enterprise data collection and annotation services, but focuses more on managed datasets than self-serve tooling. | [.md](https://openaitools.app/ko/tool/definedcrowd-com.md) |
| 8 | [Label Studio](https://openaitools.app/ko/tool/label-studio) | 137,199 | -16.1% | 가격 문의, 무료 | 깊이 있는 커스터마이징이 가능한 강력한 오픈소스 데이터 라벨링이지만, 자체 호스팅이 필요하며 기본 제공되는 관리형 엔터프라이즈 워크플로가 부족합니다. | [.md](https://openaitools.app/ko/tool/label-studio.md) |
| 9 | [Future AGI](https://openaitools.app/ko/tool/future-agi) | 121,741 | -7.8% | Freemium, Usage-based | 스스로 개선되는 AI 에이전트를 구축·시뮬레이션·평가·모니터링 | [.md](https://openaitools.app/ko/tool/future-agi.md) |
| 10 | [Maxim AI](https://openaitools.app/ko/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/ko/tool/maxim-ai.md) |

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출처: https://openaitools.app/ko/compare/scale-vs-super-annotate

More Markdown: [카테고리](https://openaitools.app/ko/categories.md) · [트래픽 순위](https://openaitools.app/ko/rankings.md) · [llms.txt](https://openaitools.app/ko/llms.txt)