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Runway

Vannus has not established which model this vendor runs, and does not infer one. Every finding below is quoted to the vendor’s own document, or marked not disclosed where the vendor publishes nothing.

AI-powered video generation and editing for creative professionals

video, generative, creative
What the vendor's own documentation says
We are building foundational General World Models that will be capable of simulating all possible worlds and experiences.
runwayml.com ↗ Vendor-sourcedQuote re-checked 14 Sep 2026
Who controls it
US corporate controlNot established — our catalogue recorded US control for this vendor, but we hold no document naming a US entity, so the claim is withdrawn until we do. This is a gap in our sourcing, not a finding about this vendor.
Trains on your dataYes, unless you opt out — on the vendor's default plan

Training and retention posture varies by plan. What we publish above describes the vendor’s default plan; enterprise, team and API agreements frequently differ, often materially, and a contract can override the published default entirely. Check your own plan and contract before relying on this row.

This is a separate question from the grade above. The grade measures resilience — whether the tool endures and whether you could leave it. This describes who controls the vendor. A tool can score modestly on one and strongly on the other, and many do.

On U.S. CLOUD Act reach specifically: the statute reaches a provider subject to U.S. jurisdiction over data in its possession, custody or control. Corporate control is a strong indicator of that and it is what we can evidence from published documents — but it is not the whole test. A company founded outside the U.S. can still contract through a U.S. entity or run substantial U.S. operations. Treat this as a starting point for your own review, not a legal determination, and take advice on anything that matters.

Who else handles your data

Runway publishes a list of the other companies it uses to process customer data. It names 27 of them, each shown below with the location the vendor lists it under, in the vendor’s own words.

Amazon Web Services, Inc. · USAGoogle LLC (Google Cloud) · USACastle Global, Inc. (Hive) · USAAnthropic, PBC · USAEleven Labs Inc. · USACartesia AI, Inc. · USAModal Labs, Inc. · USALiveKit, Inc. · USAOpenAI OpCo, LLC · USABlack Forest Labs Inc. · USARunware Ltd. · UKFreepik Company, S.L.U. · SpainByteplus Pte. Ltd. · SingaporeKling AI Pte. Ltd. · Singaporefal - Features & Labels, Inc. · USAOracle America, Inc. · USACoreWeave, Inc. · USAX.AI LLC · USAAlibaba Cloud US LLC · USADatabricks, Inc. · USANanonoble Pte. Ltd. · SingaporeIdeogram AI, Inc. · CanadaLTX Inc. · USAVEED Limited · UKMeta Platforms, Inc. · USAHanabi AI Inc. · USARecraft, Inc. · UK

Taken together those entries name at least Canada, Singapore, Spain, UK, USA. That is what our place list could match in the vendor’s own words above, so treat it as a floor rather than the whole of it — the entries themselves are the record.

These are other companies, not Runway. Where a sub-processor is listed as operating is a fact about that company. It is not a statement about where Runway keeps your data, which Vannus publishes separately and only from a document in which the vendor says so.

Read from runway.com on 2026-09-16. Every entry above is a verbatim span of that page.

This is the vendor’s own disclosure, reproduced. Vannus has not audited what any of these companies do with your data, and a list can change without notice. Treat it as a starting point for your own review, not a legal determination, and take advice on anything that matters.

Compliance the vendor states
SOC2

Taken from the vendor’s own published material. Vannus does not hold these reports and has not reviewed their scope or dates — ask the vendor for the current report before relying on any of them.

How this grade is set

Vannus publishes a nine-dimension trust framework — data sovereignty, training privacy, compliance posture, operational resilience, exit portability, and more. The heaviest criterion asks whether the tool builds its own AI or resells someone else's model; where the vendor discloses it, the grade cites the vendor's own documentation. No paid placements — scoring is walled off from affiliate revenue. See the methodology →

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Visit Runway ↗ Grade your whole stack →