NEWWhy single embeddings fail for video — and what to do instead.Why single embeddings fail for video.Read the post →

Ingest & Store

Feature Extractors

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

Vector Store (MVS)

Mixpeek Vector Store: horizontally scaled, feature-aware indexes.

Pipeline Builder

Visually compose extractors, retrievers, and transforms.

Retrieve & Analyze

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

Group scenes, faces or objects by similarity with Thompson sampling.

Encode your domain as versioned ontologies enforced at query time.

By Industry

Talent search, brand safety, creative analytics.

Scene search, recommendation, archive access.

Visual search, PDP enrichment, catalog QA.

Lecture search, transcript Q&A, content safety.

View all solutions →

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

API reference, SDKs, recipes, and architecture guides.

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

Browse supported HuggingFace models by task and modality.

See what teams are building with Mixpeek.

Education

Multimodal University

Fundamentals of multimodal retrieval, modules + certs.

Every term you need:embeddings to re-rankers.

Talks, demos, and customer sessions on demand.

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

Mission, team, and the multimodal vision.

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

Talk to sales, support, or press.

Technology and channel partner ecosystem.

White-glove 30-day production pilot for new customers.

Sign in Request Demo

Back to Dossier

March 12, 2024

How does Netflix use multimodal AI to personalize content recommendations?

Discover how Netflix's multimodal AI analyzes video content, user behavior, and contextual data to deliver highly personalized viewing experiences.

Entertainment

AI

Content Analysis

Personalization