What is Sieve?
Sieve provides video datasets for AI model development, focused on video generation, human avatars, and world modeling.
Categories include cinematic clips, talking heads, full-body humans, animated characters, real-world egocentric, and rendered egocentric footage.
Dataset offerings include 500K hours of annotated clips and a growing library spanning petabytes, available as packaged or custom datasets with sample access.
Data is processed with video understanding models and human QA to deliver training-ready, time-synced, paired, and conversational data formats.
Access options include scalable API processing, storage-bucket delivery, and compliance filters for licensing and permission management.
Typical use cases, training generative video models, building talking-head and avatar systems, developing egocentric perception pipelines, and creating world models.
Workflow, explore pre-packaged datasets, request samples, arrange dataset access, and integrate via API or direct storage delivery.
Security controls include end-to-end encryption, custom data retention policies, and SOC 2 Type 2 compliance for enterprise teams.
Sieve user reviews
Based on 1 review, 100.0% of users recommend Sieve, rated highly for value for money.
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Sieve's key features
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High-quality, training-ready video datasets curated with human QA
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Purpose-built video-understanding models for automated dataset curation and filtering
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Scalable API for high-throughput video processing and dataset delivery
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Extreme diversity of data sources (public, private, synthetic) with packaged and custom dataset options
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Next-generation data shapes (paired, time-synced, conversational, and more)
Sieve use cases
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Train photorealistic talking‑head and avatar generators using Sieve's large, time‑synced talking‑head and paired conversational datasets via API, accelerating model convergence and ensuring privacy with built‑in compliance and encryption
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Develop robust egocentric perception models for AR and assistive devices by leveraging Sieve's annotated egocentric video clips and time‑synced paired data to improve hand/gaze tracking and action recognition at scale without building custom labeling pipelines
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Build scalable world‑modeling and robotics simulation datasets using Sieve's annotated, time‑synced video streams and storage API to create realistic environment dynamics, multi‑agent interactions, and long‑horizon prediction datasets while maintaining enterprise security and compliance
Who is it for?
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Video researchers
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Avatar developers
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Perception engineers
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World modelers
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Data providers
