Twelve Labs provides a cloud‑native platform that applies multimodal AI to ingest raw video, extract visual, audio, and text signals, and generate searchable embeddings and structured metadata. Developers can integrate video search, classification, scene segmentation, and insight generation into their applications via RESTful APIs and SDKs, with scalable GPU processing and enterprise‑grade security.
Funding
Funding not disclosed
Founders
Product
Problem
Enterprises and media organizations accumulate massive volumes of raw video footage that remain unindexed and difficult to search, analyze, or repurpose. Manual review of this unstructured content is time‑consuming, error‑prone, and often infeasible at scale, limiting the ability to extract actionable intelligence.
Solution
Twelve Labs provides a cloud‑native platform built around advanced multimodal AI models optimized for video understanding. The service ingests raw video streams, extracts visual, auditory, and textual signals, and converts them into searchable embeddings and structured metadata. Developers can integrate the platform via RESTful APIs or SDKs to add video search, content classification, scene segmentation, and insight generation to their applications. The underlying models run on scalable GPU infrastructure, delivering near‑real‑time processing for large video libraries while maintaining data security and compliance.
Target Audience
The primary customers are developers and data teams at media publishers, enterprise knowledge‑management groups, and security firms that need to index, search, and derive insights from large video repositories.
Features
- Multimodal transformer models that jointly process visual frames, audio tracks, and on‑screen text to produce unified video embeddings
- Automatic transcription, object detection, activity recognition, and scene segmentation for granular metadata extraction
- Vector‑based similarity search API enabling keyword‑free retrieval of relevant video segments across petabyte‑scale archives
- Real‑time streaming ingestion pipeline with support for batch and incremental processing workloads
- SDKs for Python, JavaScript, and Go plus OpenAPI specifications for seamless integration into existing workflows
- Scalable cloud orchestration with auto‑scaling GPU clusters and built‑in rate limiting to handle variable workloads
- End‑to‑end encryption and role‑based access controls to meet enterprise security and compliance requirements