Unlock your video library with multimodal AI

What’s better than a beautifully maintained video tagging system? No tagging at all.

Index your video content with our AI and enjoy zero-setup, contextual natural language search across visuals, audio and dialogue.

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Already powering video search and indexing for companies like

Other AI systems automate tagging. We take it to the next level with something better.

The first generation of artificial intelligence video tagging systems automated the creation of tags and labels through computer vision. That still left video producers with huge tag libraries to maintain, and brittle search features.

Our bleeding-edge AI transforms everything in your footage into mathematical objects and granular multimodal descriptions, which can be searched with natural language, synonyms and close matches. We also add contextuality to give you ultra-precise search. Combine people, objects and actions to find exact moments that are impossible with labels alone.

Uploading a video to search for visual and audio

Import your videos from anywhere

Connect directly to your storage provider or upload your source video files. Our AI system will index visual and audio elements, making them easily searchable across cloud and on premises.

Your uploaded content is always private and is never used to train generative models.

Search with any level of detail

Our AI search works with any level of specificity; from settings and moods, all the way down to specific people, objects, actions, and combinations of all three.

Whether you’re looking for a particular shot or some top-level mood board filler, it’s just a search away.

Flexible search for all use-cases

Search within specific files, or explore your whole catalog. Get AI-powered recommendations for themes and topics. Find matching thematic content across multiple files. Auto-clip for social channels, and export to your editing suite.

Can your content tagging system do that without technical complexity and admin?

Save hundreds of hours every year

Logging and tagging is a time-consuming part of any content operations supply chain and – let’s be honest – not something that anyone enjoys. We believe in creating AI systems that enhance human efficiency, and free up time for valuable creative work and high ROI.

Traditional manual tagging MAM/DAM/PAM systems

Single-model AI tagging

Imaginario AI

Time to tag new footage

3x video runtime

Near-instant

Real-time (1:1 ratio)

Tag library maintenance

Requires dedicated staff

Requires periodic retraining and re-processing

Continuously learns, no upkeep

Types of content tagged

Dependent on editorial and content operations needs / time restrictions. Bound to specific taxonomies

Dependent on AI model used (usually multiple models needed adding cost and more prone to error)

All modalities: visual, audio, text, facial — down to shot level. No manual taxonomy needed.

Search accuracy

Finds entire clip with tag applied. Lacks contextual and semantic understanding

Finds clip with auto-generated tag. Limited to trained categories

Pinpoint exact frame, shot or scene containing search term

Search match types

Exact match with tag. Lacks contextual and semantic understanding

Exact match with tag (normally with broader range of tags)

Exact, semantic, and contextual — across visual, speech, and audio

Search modalities

Dependent on tagged content (usually only visuals or key words)

Single modality (visual labels or transcrips)

True multimodal: visual, audio, dialogue, facial, temporal

Backlog processing

Prohibitively expensive for legacy content

Cost scales linearly with archive size and modalities

Entire archive, flat fee

Taxonomy flexibility

Rigid, requires manual updates

Locked to generic pre-trained labels including characters and people

Custom taxonomies, adapts to your vocabulary

Integration / workflows

Siloed, manual export required

API-based, requires dev resources and monitoring.

On-prem, cloud storage, and MAM/DAM integrations.

Associated cost

Hourly labor, scales with volume

Pay per minute / hour of video

Predictable flat cost, regardless of volume

See it in action

From simple tags to complete video comprehension. All in one single platform and API.

Leading studios, broadcasters, production companies and corporate marketing teams use our system to identify shareable moments, clip and repurpose for social channels in seconds.

Make the most of your content library and engage your fans with ease.

Warner Bros. Discovery saw a

70%

time reduction in
multi-platform editing workflows

Cineverse located specific clips

75%

faster using our labelless AI search

Natural language search opens up more opportunities. Identify seasonal themes, pre-approved B-roll, age-restricted content for compliance in different markets, and much more.

Remove human biases, errors and typos. Search your footage confidently, knowing every second has been indexed to the same level of accuracy and granularity.

The easy way to ensure

consistency

across your entire video library

See what else you can do with Imaginario AI

Frequently asked questions

Is there a limit to how much I can search my library?

Our packages are based on the minutes of video content you import every month, not the number of searches. Once you have added your video content to our system, you are free to search as many times as you like, across all modalities.

What kind of things can I search for?

Our AI system understands your videos in the same way a human would, so you can search for anything that exists within your footage.

This could be something specific (such as an actor or a model of car), or something more thematic such as “winter” or “suspense”.

Our AI also understands the relationship between people, objects, places, emotions, and actions. So if you want to locate a specific shot you can combine elements, for example “a group of people running on the beach”.

How does your search system differ from traditional video object and sound recognition?

We add a layer of intelligence and contextuality over and above the previous generation of video search services, so you can add details and relational data to your searches to find exactly what you need.

For example, you’re preparing some social clips for Valentine’s Day so you want to find a specific scene where two characters kiss in a crowded street. With other visual search systems, you would be able to search for “man”, “woman”, “kiss” and maybe “crowd”. With our system, you can search for “A man and a woman kissing in a crowded street” and you will find exactly the right clip.