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Natural Language Search
& AI Metadata


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World-first, unique multi-modal AI solution making your visual assets more discoverable and more valuable.


Say “goodbye” to poor metadata, tags and restrictive taxonomies and “hello” to natural language search.

Works with your existing hardware and software including:

Our pioneering, new, AI algorithms let you simply describe what you want to see, delivering the right content, to the right people, at the right time.

Are you tired of video search problems?

Mobius Lab's customizable, efficient one-pass process creates an ultra-compact description of your video frames (the "Visual DNA") enabling natural language search, facial recognition, tagging, shot/logo detection plus accurate audio transcripts in 30+ languages.


And all of this can be achieved at up to 10x lower cost than traditional cloud-based vendors with an SDK that can be deployed in your data centre, private cloud or a hybrid of both, offering maximum flexibility and security.


Why not find out what next generation AI metadata and natural language search can do for you digital assets and schedule a no obligation demo now..."

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What people are saying

“The partnership between NOMAD and Mobius Labs ushers in a new Artificial Intelligence era where powerful video and image analysis along with speech to text conversion is the foundation of every content catalogue.”

Adam Miller, Co-founder & CEO, NOMAD

"Mobius Labs has changed the game for Influential by dramatically enhancing our visual search capabilities, reducing costs and increasing our processing speeds exponentially."

EVP Product, Influential

"Thanks to Mobius... content can be tagged when it is first ingested, or you can run the software to go through your archives and tag historical files just as quickly and efficiently."

Product Manager, EditShare

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Advanced Facial Recognition

Analyze faces based on real facial expressions not limited to 6 or 7

pre-defined emotions. Additional automatic face quality assurance guarantees optimal results.

Re-index your entire digital library without re-ingesting your original content from scratch. Effectively turn back time by adding new, trending tags at a later date. The "Visual DNA" keeps your library fresh and always relevant.

Turn Back Time

Retain total control over your content with zero compromise in data ownership and security. Our SDK works with your existing MAM and can be deployed in your data centre, private cloud or a hybrid of both.

Privacy Built-In

Lightning Fast Ingest at Scale

Intelligent Natural Language Search

Extract the "Visual DNA" at up to

70x real-time with tiny metadata storage overhead. Scale to enterprise level with industry-standard hardware whilst remaining extremely energy efficient.

Breathe new life into legacy content that’s poorly indexed with new ways to search, discover and analyze video assets. Multi-modal AI algorithms let you simply describe what you want to see.

Extract keywords from spoken content and tags from visual content. Customize visual and audio tags for your specific needs with an easily trainable model with no specialist AI skills required.

Dynamic Audio-Visual Tagging

Visual DNA Explained

Visual DNA unlocks a host of unique benefits not previously available in your MAM or DAM with traditional descriptive metadata

Unique to Mobius Labs, Visual DNA creates an ultra compact description of video frames (around 1500 times smaller than the corresponding 4k video content) at lightning speed and unlocks a host of benefits that were not previously available with traditional metadata.


With Visual DNA, one hour of video content requires just 30MB of metadata storage and can be re-indexed in less than 10 seconds for zero additional cost! Thus, archive video that has been poorly tagged or has no metadata at all becomes a thing of the past and your content library can always be kept fresh and relevant.


Why not find out what next generation descriptive AI metadata can do for your digital assets and schedule a no obligation demo now?

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<10sec

Re-index 1 hour of video at zero cost

Cost reduction vs current vendors

10x

Per hour of video content

30MB

Smaller than corresponding

4K content

1500x

Mobius Audio Explained

Traditional video tagging only focuses on visuals. With Mobius Audio you can now harness the complete potential of your content library.

Mobius Labs' cutting-edge audio tools allow you to generate noise-robust transcripts with automatic language identification and English translation from over 30 languages - all in a single pass.


Extract keywords based on spoken content in multiple languages, detect person or brand names and identify profanities without having to rely on separate natural language processing modules as typically required by traditional cloud-based systems.


Mobius audio can also detect 150+ sound classes of audio effects in your video content at a granular or high-level as needed.


Why not discover what next generation AI metadata can do for your digital library and schedule a no obligation demo now?

REQUEST A DEMO

10x

Real-time transcription

(100+ languages)

Real-time audio tagging from subtitles

100x

Languages transcribed/translated to English

30+

Audio effect

classes

150+

Future-Proof your Visual Assets with AI Metadata

The 5 Essential Steps

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Metadata Mastery

FREE training from the experts at Mobius Labs

Short videos | Webinars | Exclusive Previews

Find out more

Mobius Labs GmbH is receiving additional funding by the ProFIT program of the Investment Bank of Berlin. The goal of the ProFIT project “Superhuman Vision 2.0 for every application - no code, customizable, on-premise AI solutions” is to revolutionize the work with technical images. (f.e.) This project is co-financed by the European Fund for Regional Development (EFRE).


In the ProFIT project, we are exploring models that can recognize various objects and keywords in images and can also detect and segment these objects into specific pixel locations. Furthermore, we are investigating the application of ML algorithms on edge devices, including satellites, mobile phones, and tablets. Additionally, we will explore the combination of multiple modalities, such as audio embedded in videos and the language extracted from that audio.