Valn offers an AI-powered media asset management platform that automatically tags and indexes images, video, and audio files with contextual metadata. Users can search assets via keyword or visual similarity, retrieve them quickly, and maintain compliance through centralized metadata and audit trails. The solution integrates via APIs and webhooks with existing CMS, DAM, and marketing tools.
Funding
Funding not disclosed
Founders
Product
Problem
Organizations that handle large volumes of images, video, and audio often rely on manual tagging and folder structures, making it difficult to locate assets quickly, ensure consistent metadata, and maintain compliance with usage rights.
Solution
Valn provides an AI‑driven media asset management platform that automatically generates descriptive tags and metadata for digital assets as they are uploaded. The system indexes images, videos, and audio files in a searchable repository, enabling users to retrieve content with simple keyword queries or visual similarity searches. By automating cataloging, Valn reduces the time and labor required for manual metadata entry, improves asset reuse across campaigns, and helps ensure that assets meet licensing and compliance requirements. The platform integrates with existing content workflows and offers APIs for seamless connection to marketing, design, and publishing tools.
Target Audience
Valn is aimed at content creators, marketing teams, and enterprise media departments that need to manage large digital asset libraries efficiently.
Features
- Automatic AI tagging of images, video, and audio with contextual keywords, objects, and scene descriptors
- Full‑text and visual similarity search across all media types for rapid asset retrieval
- Centralized metadata store with version control and audit trails for compliance reporting
- Bulk import and real‑time processing pipeline that scales to millions of assets
- Open APIs and webhooks for integration with CMS, DAM, and marketing automation platforms