Multimodal feature extraction
Extract scenes, faces, objects, OCR, transcripts, speaker diarization, document layouts, fingerprints, entities, and embeddings from connected files.
Multimodal data infrastructure that turns files in object storage into searchable, structured data.
Mixpeek is a multimodal data platform for searching, classifying, and moderating video, images, audio, and documents. It connects to files where they already live, including S3, GCS, and other object storage, then extracts structured information such as scenes, faces, objects, OCR, transcripts, speaker segments, document regions, and embeddings. Those outputs become fields that applications and agents can search, filter, rank, and join.
The platform supports both managed extraction pipelines and standalone vector storage. Teams can compose multi-stage retrieval workflows that combine filtering, hybrid search, joins, and reranking. Feature extractors run in parallel and expose typed pipelines, schemas, and Studio paths for building workflows around multimodal content.
Extract scenes, faces, objects, OCR, transcripts, speaker diarization, document layouts, fingerprints, entities, and embeddings from connected files.
Search with dense vectors, sparse signals, and BM25 keyword relevance in a single retrieval workflow, including searches across video, images, audio, and documents.
Compose retrieval stages such as filtering, joining, and reranking in one request. The platform also supports retriever templates and standing queries that can trigger webhooks when new documents match.
Connect buckets and index content where it already lives. Managed plans handle extraction, embedding, and indexing, while the Mixpeek Vector Store supports bring-your-own vectors.
Use production extractors with live schemas, README documentation, and Studio paths. Supported integrations include S3, GCS, R2, Mux, LangChain, and MCP.
Map the creative elements in an ad library, search for specific moments or brand signals, group related material, and identify reusable patterns across campaigns.
Find scenes, takes, people, or spoken phrases across large video and audio collections without reviewing every file end to end.
Screen footage and other media for safety signals, route flagged results for human review, and retain the extracted evidence behind a decision.
Add image embeddings and extracted product information to commerce catalogs to support visual search, product detail page enrichment, and catalog quality checks.
Mixpeek processes video, images, audio, documents, text, and web pages. Extracted outputs can include scenes, faces, OCR, transcripts, speaker segments, document regions, entities, and embeddings.
It connects to object storage such as S3, GCS, and R2, along with integrations including Mux. The source material remains in the connected storage while Mixpeek extracts and indexes information from it.
Yes. The Mixpeek Vector Store supports bring-your-own vectors, and the platform can generate embeddings from more than 50 models. Custom model weights are offered through single-tenant arrangements.
Retrievers can combine stages such as broad recall, filtering, semantic joins, and reranking. Templates package namespaces, sources, collections, retrievers, evaluation thresholds, and review rules together.
Os dados de tráfego são apenas para referência.
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