Managing large video archives requires increasingly efficient classification and search systems. Our
solution uses artificial intelligence to generate intelligent, scalable and contextual metadata, making
all content immediately accessible and searchable.

Objective of the System

Automate the generation and association of metadata for video content, increase accuracy in the
recognition of visual, audio and text content, and improve the search and management experience of audiovisual archives.

Technologies used

– Artificial vision (object detection, face recognition, scene classification)
– Voice recognition and automatic transcription (ASR)
– NLP for generating descriptions and keywords
– Neural networks for thematic classification and sentiment analysis

Key Features

– Automatic analysis of visual and audio content
– Detection and tagging of objects, people, places, and text
– Automatic transcription and subtitling in multiple languages
– Classification by genre, tone, context, and duration
– Export to standard formats (JSON, XML, CSV)

Benefits for the Customer

– Drastic reduction in manual cataloguing time Video Metadata AI System
– Advanced semantic search in video content
– Enhancement of the archive through intelligent accessibility
– Simple integration with DAM, CMS and OTT platforms

Use Cases

– Television and film archives
– Press agencies and journalism
– Broadcast and media companies
– Law enforcement and video surveillance
– E-learning and training platforms

Proven Results

– Accuracy > 90% in facial and object recognition
– Average metadata creation time reduced by 75%
– Significant increase in content retrieval

Deployment and Integration

– Interface via REST API or web dashboard
– Batch or real-time processing options
– Multi-format video compatibility
– Cloud, on-premise or hybrid options

Intelligent metadata for video content is now a strategic element in enhancing, protecting and
fully exploiting the potential of digital archives.