NEWMVS for embeddings. Managed for files. Both on object storage.Vectors or files. Pick a path.Start →

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Vector Store (MVS)

Bring your own vectors. Dense, sparse, and BM25 search on object storage.

Managed Indexing

Connect a bucket and auto-extract scenes, faces, OCR, transcripts, and embeddings.

Build

Compose multi-stage search in <100ms: filter, join, rerank.

Feature Extractors

Typed pipelines for faces, scenes, transcripts, OCR, fingerprints.

S3, GCS, R2, Mux, LangChain, MCP, and more. Connect your stack.

Generate and store embeddings from 50+ models, then search them.

By Industry

Map, search, and reuse the moments that perform. Plugs into iconik & Mux.

Talent search, brand safety, creative analytics.

Scene search, recommendation, archive access.

Visual search, PDP enrichment, catalog QA.

Lecture search, transcript Q&A, content safety.

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By Use Case

Face & Person Search

Find anyone across video libraries in milliseconds.

IP & Copyright Detection

Logos, songs, faces: one pipeline, one report.

Visual Taste & Recs

Scene-similarity ranked recommendations with RL.

Brand & Ad Safety

Pre-publish content screening at bid-time speeds.

View all use cases →

Build & evaluate

API reference, SDKs, recipes, and architecture guides.

Browse supported HuggingFace models by task and modality.

Mixpeek vs. Pinecone, Weaviate, Twelve Labs, more.

See what teams are building with Mixpeek.

Learn

Best-of comparisons: vector DBs, embedding models, moderation APIs.

Vendor-neutral deep dives on perception, retrieval, and embeddings.

Launches, deep dives, and field notes from our engineers.

Papers behind multimodal search (MUVERA, SAM 3, and more) explained.

Every term you need: embeddings to re-rankers.

Videos, diagrams & university →

Mission, team, and the multimodal vision.

We're hiring across research, infra, and design.

Talk to sales, support, or press.

45-min working session on your data: leave with a running notebook.

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March 23, 2024

How does Netflix analyze video content for recommendations?

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