The Versos video intelligence platform unlocks revenue for studios by ethically licensing their rights-cleared video archives to the world’s top AI model builders

Earn from your archived and unused footage—without giving up your rights.

Acquire rights-cleared, structured video datasets for building and training AI models.
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Discover and package the exact video assets buyers need into AI-ready training datasets.
Learn MoreTransform raw video archives into structured, searchable training data with the Versos Intelligence Engine — built to detect, label, and segment content down to the frame.

Your entire library becomes searchable by AI-ready categories, tags, formats, and resolutions, making your content easy for AI teams to find in the marketplace.

Organize, filter, and export footage by category type, region, language or anything else — ready for training, licensing, or custom dataset assembly.


Every file in Versos carries verified ownership, licensing, and usage data — ensuring studios are protected and AI teams train on traceable, defensible content.

Every asset carries a complete record of where it came from, who owns it, and how it can be used — giving studios full transparency, defensibility, and a documented chain-of-custody for every deal.

One click shows your ownership, license terms, and usage history — making it effortless for studios to prove rights and for AI teams to confidently train on your content.
Here’s how Versos helps all sides of the video data economy connect and thrive.
Versos is a video licensing and data rights platform that turns studio archives into AI-ready datasets.We help studios, creators, and brokers monetize their full libraries — not just clips — by indexing every scene through our Library Intelligence system, verifying rights, and packaging content for AI model training, computer vision, and machine learning.With Versos, your archive becomes a searchable, rights-cleared asset ready to license into the rapidly growing AI data economy.
Versos connects AI developers with pre-cleared, machine-readable video data from professional studios and brokers.Each dataset is enriched with segment-level metadata, transcripts, and contextual tags generated through our Library Intelligence pipeline — allowing buyers to search, filter, and license content by subject, action, or visual element.This gives AI teams immediate access to diverse, structured datasets for model building, training and fine-tuning — all with transparent provenance.
AI systems learn from the data they’re trained on — and using unlicensed or scraped video exposes companies to legal and ethical risk.Versos ensures every dataset comes with verifiable rights and documented consent, protecting both the studio and the AI company.Licensed video also means higher-quality, traceable, and diverse data that supports safer, more accurate model outcomes — while ensuring creators are compensated for their work.
“Chain of Custody” is Versos’ verification framework that provides full traceability from the original source to model training use. Every file ingested is logged, fingerprinted, and linked to its rights documentation, ensuring proof of origin, usage transparency, and auditability across the data lifecycle. For studios and brokers, this means you can license with confidence; for AI teams, it means compliant, defensible training data with a clear rights trail.
Unlike stock footage sites built for media editors, Versos is designed for studios, brokers, and AI developers who need to transform entire libraries into structured, rights-cleared datasets.Through our Library Intelligence system, studios gain deep visibility into their archives — every scene is indexed, tagged, and searchable at a segment level. This enables faster discovery, packaging, and monetization of existing footage for AI training and dataset licensing.For brokers and AI teams, Versos delivers machine-readable metadata, chain-of-custody tracking, and usage reporting, turning unstructured video into compliant, traceable datasets ready for model development and fine-tuning.