Sieve

What is Sieve?

Sieve is the only AI research lab exclusively focused on video data, building the datasets and environments that frontier AI labs use to train the next generation of multimodal systems. The platform provides high-quality video, audio, image, and interaction data for frontier AI research, with hundreds of petabytes of curated multimodal data including coherent scenes with clean motion, composition, physics, and storytelling.

Key features include the complete data pipeline: Source (capturing and aggregating multimodal data across real-world, digital, and simulated environments), Filter (scoring for semantics, rights, artifacts, task quality), Index (indexing billions of videos, images, audio clips with purpose-built detectors and embeddings), Annotate (adding dense labels, pairings, temporal alignment, transcripts, action metadata, and human QA at scale), and Deliver (packaging training-ready datasets, evaluation sets, and environments for secure delivery). The platform offers public functions like sieve/autocrop, sieve/dubbing, and sieve/lipsync that can be run via API or Python client, plus custom function deployment capabilities.

Sieve is built for leading AI teams including frontier AI labs, Fortune 100 companies, and fast-growing AI startups working on generative media, robotics, computer use, world models, and agentic systems. The platform provides research-grade data through direct partnership with research teams, multimodal scale processing of millions of hours of data, custom collection based on exact capabilities teams want to improve, dense annotations including captions/transcripts/object labels/action metadata/camera signals/UI events, compliance-first filtering with licensing and consent support, and secure delivery with end-to-end encryption and SOC 2 Type 2 controls.

The platform includes a scalable API built to process millions of hours of video at any given moment, a dashboard for visualizing outputs, Python client (pip install sievedata), API access with X-API-Key authentication, and pre-packaged datasets deliverable within 1-2 days via S3-compatible storage bucket access.

Sieve's unique combination of exabyte-scale video infrastructure, novel video understanding techniques, and dozens of diverse data sources enables delivery of data with unmatched precision, quality, and speed, earning trust from the world's leading AI research teams.

Sieve pricing

Pricing model: Free

Sieve operates on an enterprise pricing model requiring a purchase agreement based on data volume, task complexity, and annotations. For the API/functions platform, there is a Starter plan at $0/month + usage with $20 free credit, public apps access, custom function deployment, and up to 3 concurrent requests. The Production plan offers usage discounts available, custom concurrency, unlimited organization seats, 24x7 customer support, dedicated Slack channel, and custom integration support. Specific function prices include Dubbing (ElevenLabs voice) at $0.535/minute processed and SieveSync lipsync at $0.50/min of generated video. GPU compute costs range from $0.40/hr (CPU) to $4.20/hr (A100 40GB). Pre-packaged datasets of 500K hours high quality diverse video clips are available via contact.

Sieve pros

• Only AI research lab exclusively focused on video data
• Provides hundreds of petabytes of curated multimodal data
• Exabyte-scale video infrastructure for processing at scale
• Delivers training-ready datasets within 1-2 days
• Supports frontier AI labs, Fortune 100 companies, and AI startups
• Offers public functions like autocrop, dubbing, and lipsync out of the box
• Python client available via pip install sievedata
• API access with simple X-API-Key authentication
• Dashboard for visualizing job outputs
• Custom function deployment capabilities
• Dense annotations including captions, transcripts, object labels, action metadata
• Compliance-first with filtering, licensing, consent, and retention support
• SOC 2 Type 2 secured with end-to-end encryption
• Custom collection based on exact model capabilities teams want to improve
• Multimodal scale processing millions of hours of video, audio, image data
• Research-grade data through direct partnership with research teams
• Secure delivery via S3-compatible storage bucket access
• Scalable API built to process millions of hours concurrently
• Before-and-after media pairs for controlled generation and editing
• Synchronized audio-visual data including video, image, speech, music, sound

Sieve cons

• Enterprise pricing requires purchase agreement based on dataset volume
• No publicly listed free tier for dataset purchases
• Custom datasets delivered on SLA rather than fixed timeline
• High concurrency requires production plan with custom setup
• Some functions like dubbing use external APIs (ElevenLabs) adding dependency
• Lipsync works best when face is arms-distance from camera facing forward
• Zero-shot lipsync has reduced quality compared to trained avatar approaches
• Dataset samples require contact form submission rather than instant access

Categories

• Code & Development

Use cases

• Transcribe Audio
• Code Assistant
• Upscale Images