# Sieve vs SuperAnnotate

Sieve records 124 monthly visits with +1.6% month-over-month growth and Contact for Pricing pricing. SuperAnnotate records 386,034 monthly visits with +37.4% growth and Free Trial, Contact for Pricing pricing.

| Metric | [Sieve](https://openaitools.app/tool/sieve) | [SuperAnnotate](https://openaitools.app/tool/super-annotate) |
| :--- | :--- | :--- |
| Website URL | https://www.sieve.ai | https://www.superannotate.com |
| Categories | AI API, AI Dubbing, AI Video Translator, AI Video Editor | AI Workflow, AI Developer Tools, AI Project Management |
| Pricing Model | Contact for Pricing | Free Trial, Contact for Pricing |
| Monthly Visits | 124 | 386,034 |
| MoM Growth Rate | +1.6% | +37.4% |
| Primary Market | Global | United States |
| Direct Visits | 54 | 248,258 |
| Review Score | 4.1 | 4.6 |
| Saved Count | 0 | 0 |
| Supported Platforms | Website | Website |

## Sieve

Sieve began life as a video API company offering endpoints for translation, dubbing, background removal, lipsync, autocrop and transcription. That product line has since been superseded: the company published an announcement titled "Reintroducing Sieve" describing its transition from video APIs to supplying multimodal data at petabyte scale, and the original sievedata.com domain now resolves to sieve.ai.

Today Sieve operates as a data lab for what it calls real-world intelligence. Instead of selling individual API calls, it works with frontier AI companies to design, capture, annotate and deliver high-quality training and evaluation data. Its public offerings include egocentric first-person video of economically valuable work with hand-pose and sensor annotations, custom multi-camera studio recordings, simulated and real-world robotics evaluations, virtual-world capture with synchronised control inputs and camera metadata, and datasets targeting motion, causality and spatial reasoning.

Underneath the data products sits serious infrastructure. Sieve has published engineering work on embedding one billion videos and querying tens of billions of vectors, which is the kind of stack you need to make petabyte-scale audiovisual archives searchable for model training. The practical route in is a conversation rather than a signup: visitors are pointed at "Talk to us" and "Request data" flows, and the company is actively hiring researchers and engineers.

**Pricing & Plans:** 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.

**Strengths:** 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

**Limitations:** 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/tool/sieve.md)

## SuperAnnotate

SuperAnnotate positions itself as end-to-end AI data infrastructure rather than a single-purpose labeling tool. The core of the product is a highly customizable annotation surface that handles image, video, text, and audio projects in the same workspace, so teams that train multimodal models do not have to stitch together several vendors or build internal review tooling from scratch. Around the editor sit data curation and exploration features, analytics for tracking throughput and inter-annotator agreement, and project management for organizing large distributed labeling workforces.

Beyond the software layer, SuperAnnotate offers an orchestration engine with metered compute hours, plus access to its own data-operations specialists who can run high-volume or unusually complex annotation programs on the customer's behalf. Managed-service elements such as single sign-on, dedicated Slack channels, a named customer success manager, a dedicated solutions engineer, and AI DataOps consulting are gated behind higher tiers, which reflects the enterprise orientation of the platform.

SuperAnnotate is commonly used upstream of model training and fine-tuning, which is why it markets results such as faster annotation cycles and higher model F1 scores. It also supports the data-centric workflows around RLHF, SFT, RAG evaluation, and dataset versioning that modern generative AI teams depend on. Because it handles security, permissions, and auditability at an enterprise grade, it tends to be adopted by organizations that need governance as much as speed.

**Pricing & Plans:** 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.

**Strengths:** 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

**Limitations:** 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/tool/super-annotate.md)

## Frequently Asked Questions

### How do Sieve and SuperAnnotate compare in monthly traffic?

Sieve has 124 monthly visits, while SuperAnnotate has 386,034. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Sieve has a month-over-month growth rate of +1.6%; SuperAnnotate has +37.4%.

### How does pricing compare?

Sieve: Contact for Pricing. 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. SuperAnnotate: Free Trial, Contact for Pricing. 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

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [Roboflow](https://openaitools.app/tool/roboflow) | 1,431,204 | +6.6% | Freemium, Contact for Pricing | Build, train, and deploy computer vision for the physical world | [.md](https://openaitools.app/tool/roboflow.md) |
| 2 | [ImageKit](https://openaitools.app/tool/imagekit) | 947,721 | -13.7% | Freemium, Paid, Contact for Pricing | Real-time image and video APIs, agentic DAM and creative automation in one platform | [.md](https://openaitools.app/tool/imagekit.md) |
| 3 | [Labelbox](https://openaitools.app/tool/labelbox) | 762,803 | -22.8% | Contact for Pricing | Strong enterprise data labeling and agentic automation, but offers a distinct collaborative interface and pricing structure. | [.md](https://openaitools.app/tool/labelbox.md) |
| 4 | [Appen](https://openaitools.app/tool/appen-com) | 665,840 | +0.2% | Contact for Pricing | Extensive human-validated training datasets and alignment services, but lacks SuperAnnotate's self-serve software platform flexibility. | [.md](https://openaitools.app/tool/appen-com.md) |
| 5 | [Scale](https://openaitools.app/tool/scale) | 616,915 | +12.5% | Contact for Pricing | The data, evaluations and systems behind AI that has to be right. | [.md](https://openaitools.app/tool/scale.md) |
| 6 | [AI or Not](https://openaitools.app/tool/ai-or-not) | 375,863 | +12.3% | Freemium, Contact for Pricing | Multi-modal AI detection API that flags synthetic images, text, audio, video and deepfakes | [.md](https://openaitools.app/tool/ai-or-not.md) |
| 7 | [Weights & Biases (CoreWeave Forge)](https://openaitools.app/tool/prompts) | 315,624 | -80.2% | Freemium, Contact for Pricing, Free | Exceptional for ML experiment tracking and LLM evaluation, but does not provide traditional computer vision data labeling environments. | [.md](https://openaitools.app/tool/prompts.md) |
| 8 | [Encord](https://openaitools.app/tool/encord-com) | 244,204 | +9.4% | Contact for Pricing | Excellent multimodal data infrastructure for computer vision, but lacks some of SuperAnnotate's broader enterprise project management tools. | [.md](https://openaitools.app/tool/encord-com.md) |
| 9 | [AI/ML API](https://openaitools.app/tool/ai-ml-api) | 232,946 | -20.1% | Pay-as-you-go credits (free to start); enterprise custom pricing on request | One universal API for 500+ AI models and 1,000+ agentic tools | [.md](https://openaitools.app/tool/ai-ml-api.md) |
| 10 | [Memories.ai](https://openaitools.app/tool/memories-ai) | 188,127 | -14.6% | Freemium, Contact for Pricing | Video data infrastructure for physical AI and robot training | [.md](https://openaitools.app/tool/memories-ai.md) |

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

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