Video Search

Multimodal Embedding Model

A cutting-edge multimodal embedding model designed specifically for video search. Our model understands visual content, audio, speech, and context to deliver accurate semantic search results across your entire video library.

Video Search - Multimodal AI

Key Features

Multimodal Understanding

Comprehensive analysis of video, audio, and text. Our model processes visual scenes, spoken words, background sounds, and on-screen text simultaneously for complete understanding.

Semantic Search

Search using natural language queries. Find content by describing what you're looking for, not just matching keywords. Understand context and intent behind queries.

Real-time Performance

Lightning-fast indexing and retrieval. Process new videos in seconds and get search results instantly, even across millions of videos in your library.

Scalable Architecture

Handle video libraries of any size. Our infrastructure scales automatically to meet your needs, from thousands to millions of videos with consistent performance.

Easy Integration

Simple REST API with SDKs for all major languages. Integrate video search into your application in minutes with comprehensive documentation and examples.

Enterprise Security

Bank-level encryption and compliance. Your video data is secure with SOC 2 compliance, end-to-end encryption, and role-based access controls.

Use Cases

Media & Entertainment

Find specific scenes, quotes, or moments across vast archives. Enable content creators to quickly locate footage for editing and repurposing.

E-Learning

Help students find exact topics within lecture videos. Create searchable knowledge bases from educational content.

Security & Surveillance

Quickly locate incidents or persons of interest. Search through footage using natural language descriptions of events.

Corporate Training

Make training materials instantly searchable. Employees can find relevant procedures and demonstrations in seconds.