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    Extract, index, retrieve: the whole loop

    Extract, index, retrieve: the whole loop

    The multimodal data warehouse in one flow: extract signals from media (faces, scenes, speech, on-screen text, embeddings) so pixels become rows at ingest, index that meaning next to the bytes so it is queryable forever after one read, and retrieve by meaning with hybrid search and reranking — served to humans and agents the same way. Extract, index, retrieve; everything else is implementation detail.
    Extract, index, retrieve: the whole loop

    Twelve posts in this series, one picture.

    Most of what a company knows is unstructured and unqueryable. Embeddings turn meaning into coordinates, so search becomes distance. Files decompose into moments, extraction turns pixels and audio into signals, because storage alone answers nothing. Chunking decides what's findable. Hybrid retrieval catches what vectors and keywords each miss. Reranking buys precision. RAG hands the result to a model. Eval tells you whether any of it actually works.

    Run that as one system instead of ten separate vendor decisions and you get a multimodal data warehouse: media in, structured searchable meaning out, humans and agents querying it the same way.

    That's what we're building at Mixpeek. Not a vector database, not a RAG framework. The warehouse where the whole loop lives.

    Three verbs the whole time: extract, index, retrieve. Everything else is implementation detail.

    Run this on your own data

    Mixpeek turns video, images, audio, and documents in your object storage into searchable, timestamped results through one API.

    Search your own data, free