Description
Sieve is a multimodal data lab that provides curated video, audio, image, and interaction data for training frontier AI models. It captures and aggregates data across real-world, digital, and simulated environments, then scores it for semantics, rights, artifacts, and task quality before packaging it for delivery.
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The platform indexes billions of videos, images, audio clips, and interaction traces using purpose-built detectors and embeddings, and adds dense annotations such as captions, transcripts, object labels, action metadata, camera signals, and human QA at scale. Teams can browse ready-to-use datasets or request custom collection targeted at specific model capabilities.
Sieve works directly with research teams to scope volume, distributions, metadata, licensing, QA, and delivery format, and supports compliance requirements including filtering, consent, and retention. Datasets and evaluation sets are delivered securely, backed by end-to-end encryption and SOC 2 Type 2 controls.
- CategoryMachine Learning Platforms
- Pricing ModelContact sales
- DeploymentCloud
- PlatformsWeb
Sieve's Core Features
Curated multimodal video, audio, image, and interaction datasets
Data sourcing across real-world, digital, and simulated environments
Quality filtering for semantics, rights, artifacts, and task quality
Indexing with purpose-built detectors and embeddings
Dense annotations: captions, transcripts, labels, and action metadata
Custom data collection scoped to specific model capabilities
Compliance-first filtering, licensing, consent, and retention support
Secure delivery with encryption and SOC 2 Type 2 controls
How to use Sieve?
Explore capabilities: Browse ready-to-use datasets or describe what your research team needs.
Receive samples: Request samples across video, audio, image, computer use, or interactive environments.
Scope the dataset: Work with the Sieve team to define volume, distributions, metadata, licensing, QA, and delivery format.
Purchase access: Enter a purchase agreement based on data volume, task complexity, and annotations.
Receive delivery: Get pre-packaged datasets within days or custom data and environments on an SLA.
Sieve's Use Cases
- Model training datasets
- Evaluation sets
- Video editing and generation data
- Interactive and computer-use environments
