# Scale vs Sieve Scale는 월간 방문 616,915, 전월 대비 성장률 +12.5%, 가격 문의 가격 모델을 기록합니다. Sieve는 월간 방문 124, 성장률 +1.6%, 가격 문의 가격 모델을 기록합니다. | 지표 | [Scale](https://openaitools.app/ko/tool/scale) | [Sieve](https://openaitools.app/ko/tool/sieve) | | :--- | :--- | :--- | | 웹사이트 URL | https://scale.com | https://www.sieve.ai | | 카테고리 | AI 개발자 도구, Large Language Models (LLMs), AI 모델, AI Agent | AI API, AI 더빙, AI 영상 번역기, AI 영상 편집기 | | 가격 모델 | 가격 문의 | 가격 문의 | | 월간 방문 수 | 616,915 | 124 | | 전월 대비 성장률 | +12.5% | +1.6% | | 주요 시장 | 미국 | 글로벌 | | 직접 방문 | 191,408 | 54 | | 리뷰 점수 | 4.7 | 4.1 | | 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) ## Sieve Sieve is a data lab that supplies multimodal video, audio and interaction datasets — egocentric demonstrations, multi-camera studio recordings, robotics evaluations and large-scale media — to frontier AI teams. **가격 및 요금제:** No public price list. Sieve is positioned as a custom engagement led by a "Talk to us" / "Request data" contact flow, so commercial terms are scoped per project, data volume and capture complexity. Earlier self-serve API pricing is no longer published. - **Egocentric data capture:** First-person recordings of economically valuable physical work, paired with hand-pose, motion and synchronised sensor annotations. - **Studio and custom rig recordings:** Multi-camera video and audio collection with bespoke rigs and controlled environments built to a client's specification. - **Robotics evaluations:** Both simulated and real-world test suites that measure how well robot policies perform across tasks and conditions. - **Large-scale media infrastructure:** Petabyte-scale synchronised video and audio datasets, including published engineering work on embedding a billion videos for retrieval. - **Real-world reasoning datasets:** Datasets and benchmarks targeting motion, causality and spatial relationships for models that must reason about the physical world. **강점:** Deep specialisation in hard-to-collect embodied and egocentric data; In-house research and infrastructure proven at billion-video scale; Offers evaluations alongside datasets, not just raw media; Works directly with frontier labs, which signals high data quality standards **한계:** Pricing is quote-based, so there is no self-serve cost transparency; Most offerings require an engagement rather than instant API signup; Documentation for the older video API suite is no longer reachable at the previous docs domain; Overkill for teams that only need a single simple video-processing endpoint [Profile (Markdown)](https://openaitools.app/ko/tool/sieve.md) ## 자주 묻는 질문 ### Scale과(와) Sieve의 월간 트래픽은 어떻게 비교되나요? Scale의 월간 방문 수는 616,915이고, Sieve는 124입니다. 트래픽 추정치는 제품 품질이 아니라 사용자 규모를 나타냅니다. ### 두 도구의 성장률은 어떻게 비교되나요? Scale의 전월 대비 성장률은 +12.5%이며, Sieve는 +1.6%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. Sieve: 가격 문의. No public price list. Sieve is positioned as a custom engagement led by a "Talk to us" / "Request data" contact flow, so commercial terms are scoped per project, data volume and capture complexity. Earlier self-serve API pricing is no longer published. ## 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 | 물리적 세계를 위한 컴퓨터 비전을 구축하고 학습하고 배포하세요 | [.md](https://openaitools.app/ko/tool/roboflow.md) | | 2 | [ImageKit](https://openaitools.app/ko/tool/imagekit) | 947,721 | -13.7% | 무료+유료, 유료, 가격 문의 | 실시간 이미지·동영상 API, 에이전트 DAM, 크리에이티브 자동화를 한곳에 | [.md](https://openaitools.app/ko/tool/imagekit.md) | | 3 | [Labelbox](https://openaitools.app/ko/tool/labelbox) | 762,803 | -22.8% | 가격 문의 | Scale의 핵심 어노테이션 사업과 비슷하게 기업용 데이터 라벨링 및 학습 데이터 큐레이션에 집중합니다. | [.md](https://openaitools.app/ko/tool/labelbox.md) | | 4 | [SuperAnnotate](https://openaitools.app/ko/tool/super-annotate) | 386,034 | +37.4% | 무료 체험, 가격 문의 | 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 | [.md](https://openaitools.app/ko/tool/super-annotate.md) | | 5 | [AI or Not](https://openaitools.app/ko/tool/ai-or-not) | 375,863 | +12.3% | 무료+유료, 가격 문의 | 이미지·텍스트·오디오·영상·딥페이크를 판별하는 멀티모달 AI 탐지 API | [.md](https://openaitools.app/ko/tool/ai-or-not.md) | | 6 | [Weights & Biases(CoreWeave Forge)](https://openaitools.app/ko/tool/prompts) | 315,624 | -80.2% | 무료+유료, 가격 문의, 무료 | 하나의 연결 환경에서 AI 모델과 에이전트를 추적·평가·배포하세요. | [.md](https://openaitools.app/ko/tool/prompts.md) | | 7 | [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) | | 8 | [Encord](https://openaitools.app/ko/tool/encord-com) | 244,204 | +9.4% | 가격 문의 | 컴퓨터 비전과 피지컬 AI 팀을 위한 멀티모달 데이터 레이어 | [.md](https://openaitools.app/ko/tool/encord-com.md) | | 9 | [AI/ML API](https://openaitools.app/ko/tool/ai-ml-api) | 232,946 | -20.1% | Pay-as-you-go credits (free to start); enterprise custom pricing on request | 500개 이상의 AI 모델과 1,000개 이상의 에이전트 도구를 하나의 API로 | [.md](https://openaitools.app/ko/tool/ai-ml-api.md) | | 10 | [Memories.ai](https://openaitools.app/ko/tool/memories-ai) | 188,127 | -14.6% | 무료+유료, 가격 문의 | 피지컬 AI와 로봇 학습을 위한 영상 데이터 인프라 | [.md](https://openaitools.app/ko/tool/memories-ai.md) | --- 출처: https://openaitools.app/ko/compare/scale-vs-sieve 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)