speaker identification indexing Archives

AI applications

Our AI applications

Deep Media Analyzer

Gain powerful insights from your media assets

Deep Model Customizer

Create your own models in seconds

Deep Collector

Enrich all your media assets with valuable metadata

Deep Live Hub

AI-based live subtitling and translation

Deep Indexer

Index unknown individuals to enrich your media assets

Deep Explorer

Explore knowledgeable relations in your media assets

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Solutions
by use case

Improving visual search

Equality and diversity insights

Individual person identification 

Identification of speakers

Building a face recognition dataset

Building a speaker dataset

Similarity and reverse search

Duplicate detection

Speeding up research time

Improving video recommendations

Automated thumbnails

SDR to HDR conversion

Contextual Tagging

See all use cases

by customer story

Arvato Systems

Bayerischer Rundfunk

City of Heilbronn

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Our experience with general AI solutions has been that you often fail to identify the necessary objects in your own content. Creating training data and managing datasets is complex and time consuming. DeepVA's integration with our media service has shown us that customisable AI can be intuitive and straightforward within the already familiar MAM interface.

Ralf JansenSoftware Architect at Vidispine

The use of artificial intelligence in the city archive has met our expectations and provides real added value - not only for archival tasks, but also for interested citizens.

Miriam EberleinProject manager
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New features and improvements in DeepVA: August 2024 Changelog

We are pleased to present our latest changelog, which shows the current progress and improvements of our revolutionary software DeepVA.

New features and improvements in DeepVA: Spring 2024 changelog

We are pleased to present our latest changelog, which shows the current progress and improvements of our revolutionary software DeepVA.

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The project has indirectly received funding from the European Commission’s Horizon 2020 Framework Programme through the STADIEM project (Grant Agreement 957321)

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