Danbi vs QMedia

Danbi is an API for indexing video archives so teams can search for moments in plain English and AI agents can query the archive through MCP. Its index can structure faces, spoken words, actions, objects, on-screen text, and timecodes. Searches return exact moments that can be played, cited, exported, or shared, with subtitles and retention listed for the archive product. Danbi can run beside a media asset management system: that system supports human catalog browsing while Danbi handles AI-assisted retrieval and agents. Deployment uses the customer’s own hardware and infrastructure by default, and indexed results remain on infrastructure the customer controls. Selected fragments that benefit from third-party models may be sent out. The free recording trial processes files on Danbi’s hardware, accepts recordings up to 90 minutes and 2 GB, and deletes them two hours after they are ready. Danbi offers visual, audio, and multimodal search.

QMedia is an open-source multimedia AI search engine for content creators. It searches and extracts information from text, images, and short videos, combining those formats in a multimodal retrieval and question-answering system. Its web service displays content and sources as cards with image, text, and short-video breakdowns. The project can run locally for offline search and question answering over private data. The web service, RAG search and Q&A service, and image, text, and video model service can be deployed separately. The standalone model service offers an API for image and text encoding, video transcription, and image OCR. Documented model options include CLIP, BGE, Qanything OCR, LLaVA, and Faster Whisper, with local Ollama model switching. Google content search is configurable but disabled by default, as is video service use in the RAG server configuration. The RAG service depends on a separate mm_server service. QMedia is self-hosted, available through its web service, and licensed under MIT.