Sieve’s March 4, 2026 company update explains its shift from video APIs to supplying multimodal datasets end to end. Confirm any legacy API agreement separately from the current data-lab offering. Read the source ↗

Data and AI platforms / Sieve Multimodal Data Lab alternative

A Sieve AI alternative for the agent working with multimodal data

Sieve now describes itself as a multimodal data lab supplying video, audio, image and interaction datasets and custom environments. Its March 2026 company update explains the shift from video APIs to end-to-end data supply. The present offering is adjacent to the Linux runtime an agent uses to inspect, transform or evaluate that data.

Start building Compare capabilities ↓

Reviewed 2026-10-19 · Published by the Sandbox0 team

When Sieve Multimodal Data Lab fits

Sieve fits research teams purchasing curated training data, annotations, evaluation sets or custom collected environments. Those datasets, rights and collection services are not supplied automatically by an agent sandbox.

When to consider Sandbox0

Choose Sandbox0 for compatible Linux agents processing or coordinating data work with durable installed tools, configuration and files across the whole writable RootFS, online growth and supported paused files. Retain required datasets and rights.

Capabilities

Sieve Multimodal Data Lab and Sandbox0: what persists?

Feature comparison with documentation and verification status
Capability	Sieve Multimodal Data Lab	Sandbox0
Environment and runtime lifetime	Sieve Multimodal Data LabNot established in this review	Sandbox0ttl and hard_ttl default to 0 (disabled). Configure idle pause and deletion policies for the same persistent sandbox identity; an idle running sandbox still accrues compute charges.Read documentation →
Persistent files	Sieve Multimodal Data LabDataset delivery and negotiated retention are established, but a general retained writable guest disk is not.View evidence ↗	Sandbox0The writable RootFS survives successful checkpoints, including software, system configuration, dependencies, and user data.Read documentation →
Whole RootFS	Sieve Multimodal Data LabCustom research datasets/environments do not establish full mutable customer OS filesystem persistence.View evidence ↗	Sandbox0Persistence extends beyond /workspace to paths such as /usr/local, /etc, and /home. Runtime tmpfs and virtual filesystems are excluded.Read documentation →
Release compute, keep state	Sieve Multimodal Data LabA general-purpose agent machine pause/resume lifecycle is not established by the current data offering.View evidence ↗	Sandbox0Pause compute between tasks; resume on available capacity. Default resume starts fresh processes from the saved filesystem.Read documentation →
Memory and process state	Sieve Multimodal Data LabDataset and environment delivery do not establish arbitrary guest RAM/process checkpoint restoration.View evidence ↗	Sandbox0Experimental memory checkpoints can preserve compatible process state. Use memory: true on both pause and resume on a compatible deployment. A filesystem checkpoint alone does not preserve running processes.Read documentation →

Online RootFS growth

On growth-enabled images, Sandbox0 automatically expands the writable RootFS as free space runs low, within a configured sparse logical ceiling up to 64 TiB. Agent processes keep running. Growth is enabled in the qualified Cloud region; confirm activation for other regions. Existing images and snapshots retain their captured storage geometry. The ceiling is logical capacity, not preallocated host disk.

Dataset volume and negotiated data delivery are not automatic online growth of a customer-owned writable Linux RootFS. Plan data supply independently from the agent’s execution storage.

Files while compute is paused

Sandbox0's Files API reads persistent files without resuming compute. Filesystem-only pauses also permit edits; retained-memory pauses are read-only and reject mutations with 409. SSH, SFTP, file watching, and runtime-only mounts require running compute.

See paused file operations →

The current product is data supply rather than a generic video API host

Sieve’s company update describes moving from video understanding/editing APIs toward supplying datasets end to end. Current delivery is scoped around media and interaction data, metadata, licensing, quality assurance and environment requirements. Historical API or GPU price assumptions should not be used as the current data-product tariff.

Source 1 ↗Source 2 ↗

Delivery and retention are agreed for the dataset

The current workflow scopes volume, distributions, annotations, delivery format and a purchase agreement. Packaged datasets and custom delivery SLAs are data-service terms; they do not establish an arbitrary customer-controlled writable OS machine, no-wake filesystem access or saved process memory.

Source 1 ↗

An interactive environment is not automatically a general Linux sandbox

Sieve mentions computer-use, interactive-world and evaluation environments as part of data and research work. Confirm the exact environment access and retention in the project scope rather than assuming those words imply a general-purpose persistent agent computer.

Source 1 ↗Source 2 ↗

Pricing

Compare billing models, then price your workload

CPU allocation, memory, billing minimums, disk, plan fees, and supported workload differ. These meters are not equal-performance machine quotes. Confirm region, resource units, and included allowances before estimating a total.

Sieve Multimodal Data Lab

Pricing reviewed 2026-10-19

Packaged datasets: Purchase agreement by data volume and scope; Rate source ↗
Custom data and environments: Quote by task complexity, annotation and delivery requirements; Rate source ↗
Current general Linux compute tariff: Not established by the data-product offer; Rate source ↗

No numeric current public data price is published in the reviewed offer. Scope licensing, quality assurance, custom collection, retention and delivery separately; former video API or hardware-second prices do not price these agreements.

Check current Sieve Multimodal Data Lab pricing ↗

Sandbox0

$0.015/GiB-hour compute (billed by the second at approximately $0.000004167/GiB-second), plus $0.02/GiB-month of retained incremental RootFS and memory checkpoint data. Shared base images and platform recovery retention are excluded; paused sandboxes accrue storage charges only.

Compute / GiB-hour: $0.015
Retained data / GiB-month: $0.02
Paused compute: $0.00

A 4 GiB agent, 100 running hours

$6.00 compute

4 GiB × 100 hours, billed by the second. Keeping 20 GiB of billable incremental data for a full billing month adds $0.40. CPU is derived from memory by the platform; choose a tier that fits your workload.

Understand storage billing →

Before migrating from Sieve Multimodal Data Lab

Identify legacy API dependencies, purchased datasets, usage rights, annotations, environment access and delivery obligations.
Retain or replace required data services and port compatible Linux processing tools with verified inputs and outputs.
Test data quality and model evaluations separately from agent system retention, growth, paused files and execution costs.

Common questions

Is Sandbox0 a drop-in Sieve Multimodal Data Lab replacement?

Evaluate API compatibility and product scope. These products serve different core workflows, so a change may require a different architecture.

Does keeping files also keep a running agent?

Filesystem state and volatile process state are separate. Sandbox0 requires explicit compatible memory checkpoints to preserve running processes; its default filesystem resume starts fresh processes.

Sources and review scope

The Boat team's Battleships directory is the discovery source. References below describe the product and plan discussed on this page. Check current availability, regional terms and billing units before migrating. Where the cited material does not establish a capability or price, the comparison identifies that uncertainty.

Battleships research record ↗www.sieve.ai/blog/reintro ↗www.sieve.ai/ ↗www.sieve.ai/about ↗Sandbox0 RootFS capacity →

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