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MLtwist vs Scale AI, Labelbox, and SuperAnnotate

Four ways to get labeled training data. Here's how they differ on who does the work, who owns the vendor, and what you get back.

Criterion MLtwistScale AILabelboxSuperAnnotate
What you buy Labeled, human-verified training sets — staffed by our team, yours, or bothManaged data labeling and evaluation, weighted toward frontier-model and defense workLabeling software, plus its Alignerr expert networkAnnotation software, plus a vetted workforce and vendor marketplace
Ownership Independent, venture-backedMeta holds a 49% non-voting stake (June 2025)Independent, venture-backedIndependent, venture-backed
Use your own annotators Yes — in our tool, or alongside our teamPrimarily a managed serviceYesYes
Work in the labeling tool you already use Yes — we run and QA work in third-party toolsIts own platformIts own platformIts own platform
Lineage record with every delivery Data ID Card on every versionAsk the vendorAsk the vendorAsk the vendor
Security screening and 3D scan data Yes — TSA and Sandia programsAsk the vendorAsk the vendorAsk the vendor
Public sector buying Carahsoft, Google Cloud Marketplace, directEstablished federal contractsAsk the vendorAsk the vendor
Best fit Regulated, multimodal programs that need a managed team and an audit trailFrontier labs and large defense programsTeams that want to run labeling themselves on softwareTeams that want software and a choice of workforce vendors

Based on public reporting and vendor materials as of September 2026. "Ask the vendor" means we couldn't confirm it publicly — not that they don't offer it. Spot an error? Tell us and we'll fix it.

Looking for a Scale AI alternative?

Why teams choose MLtwist

Neutrality

After Meta's 49% stake in Scale AI, Google and OpenAI reportedly pulled back over concerns about exposing their roadmaps to a rival. MLtwist is independent and venture-backed.

Fit

Most large vendors now chase frontier-model data. MLtwist focuses on the messy, regulated data — security scans, drone video, low-resource languages — that generic pipelines handle badly.

Control

Keep your own experts in the loop, keep your data in your bucket, and keep a Data ID Card for every version. Switching teams or tools doesn't mean rebuilding your pipeline.

See how your program would run on MLtwist

Tell us what you're labeling. We'll scope it with our team, yours, or both — and deliver it versioned, in your format.

Also available through Carahsoft and Google Cloud Marketplace.