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AI-powered media management platform for searching, organizing, editing, and exporting media files.

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About this tool

Cosmos is an AI-driven media management platform, positioned as the "sales layer" for video production companies, built on top of the footage archives teams have already shot.

Purpose: To help video companies find suitable past work faster, enabling sales teams to win more deals using completed projects. The material points out that when a prospective client asks, "Do you have work similar to ours?", most production companies often need 24 hours to respond—producers search through hard drives, find approximate content, and then send out a messy pile of links; by then the client may have moved on elsewhere, or the examples found may not be a good fit. Sales representatives cannot show relevant work at the moment the client makes the request, so prospective clients can only decide based on what happens to be displayed on the website, while the material that could actually win the deal sits unused in the archive and is never shown.

Main capabilities: Cosmos runs where the user's footage archive is located, serving as an access layer on top of the archive. The post-production team can control which content is indexed, how it is tagged, and which content can be shared externally; the sales team gains fast, self-service on-demand access to retrieve suitable work at any time. The platform is built on the creators' more than ten years of experience in computer vision and video systems.

How to use: The material only mentions that the sales team can access indexed and tagged footage through self-service, and that the post-production team is responsible for configuring indexing and tagging, as well as managing external sharing permissions. The specific operating process, interface, and integration methods are not yet provided.

Applicable scenarios: For video production companies, especially teams whose sales teams need to frequently show past cases to prospective clients but whose footage retrieval efficiency is low. The material emphasizes that its goal is to solve the problem of missed business opportunities caused by time-consuming archive retrieval.

Limitations: The material does not provide supported media file formats, platform compatibility, pricing and charging models, deployment methods, language support, or specific usage steps. The platform's specific technical implementation details, the specific operations of indexing and tagging functions, and integration with other tools are also not yet provided.