Cloudglue provides a video‑native API that converts raw video into searchable, structured context for AI applications. Developers can use its endpoints to extract entities, segment scenes, index content, and enable chatbot or RAG features with playable video citations, as well as run bulk analysis and reporting across large video libraries, all with a simple SDK and credit‑based pricing.
Funding
Funding not disclosed
Founders
Product
Problem
Developers building AI applications often struggle to extract structured information from large volumes of video, making it difficult to enable search, reasoning, and analytics across video content at scale.
Solution
Cloudglue offers a video‑native API that transforms raw video into searchable, structured context for AI systems. By handling tasks such as scene segmentation, entity extraction, and indexing, the platform lets developers add video‑aware capabilities with minimal code. The service supports chatbot and retrieval‑augmented generation (RAG) use cases, providing playable citations for answers drawn from video. It also enables bulk analysis and reporting across thousands of hours of footage, and offers flexible schema definitions to ensure consistent data extraction. All interactions are metered via a credit system, allowing developers to scale usage according to their needs.
Target Audience
Primary customers are developers and product teams building AI‑powered chatbots, knowledge bases, analytics dashboards, or any application that needs to reason over video content at scale.
Features
- API endpoints for uploading video, automatic scene segmentation, and entity collection indexing
- Schema‑driven extraction that returns consistent, structured data (e.g., timestamps, objects, speakers)
- Search API to retrieve relevant videos or specific segments based on textual queries
- Chat completion endpoint that generates answers with playable video citations for RAG applications
- Bulk analysis tools for aggregating insights and generating reports across large video libraries
- Credit‑based usage model with per‑minute pricing, enabling predictable scaling
- Simple SDK integration requiring only a few lines of code to start processing video