A digital archivist: analyzes audio & video, writes scene descriptions and catalogs your media
Multimedia Intelligent Archive is a multimodal audio & video analysis engine that behaves like a professional archivist: it watches, listens to and reads your media files, segments them into scenes, writes a textual description for each scene and records everything as a structured catalog — an archive searchable in natural language.

Multimodal analysis means all signals are fused into one unified timeline: visuals (scenes, shots, keyframes, objects, people, logos), speech (Persian/English transcription with speaker diarization), audio (sound events) and on-screen text (titles, captions, slides). The result is a precise description of every moment of the media, with timecodes and searchable identifiers.
For broadcasters, news agencies, archive centers and content teams, thousands of hours of untagged footage mean lost assets: finding one specific scene takes hours of manual review. This system turns that into a question — "find the scene where the speaker talks about pricing while a chart is on screen" — the same pattern global tools such as Azure AI Video Indexer and Twelve Labs bring to media archives; the difference is that here Persian analysis, Persian description and Persian search are at the center of the design.
Deployment runs on your own infrastructure and media data never leaves the organization. The output (structured catalog with timecodes, summaries, people, topics and keywords) is exposed via API to your existing media asset management (MAM/DAM) or archive systems.