Cloudglue

CloudGlue: Structured Video Data for AI

CloudGlue transforms video and audio content into structured data, ready for integration with Large Language Models (LLMs). Designed for developers, it addresses the challenge of converting video libraries into AI-ready formats.

Core Capabilities:

• Video-to-Structured Data Conversion: CloudGlue converts videos and audio into structured data formats.
• RAG System Building: Enables the creation of Retrieval-Augmented Generation (RAG) systems leveraging video data.
• Aggregate Video Analysis: Facilitates the running of aggregate analysis on collections of videos.
• Chatbot and RAG Integration: Enables the creation of chatbots that answer questions based on video content via RAG.
• Video Search: Supports the ability to search across video libraries to locate and retrieve relevant videos.
• Granular Control: Offers control over the level of detail in the structured data generated.

Technical Approach:

• Single API Call: Provides a single API call for managed video Q&A.
• Segment-by-Segment Control: Allows for full control over handling embeddings, on a segment-by-segment basis.
• Transformation Speed: CloudGlue transforms approximately 50 minutes of video into LLM-ready data within 3 minutes.
• Indexing & Responses: Supports quick indexing and responses, irrespective of the library size.
• Scalable Insights: Supports scaling from quick transcripts to full multimodal insights.

Target Audience & Use Cases:

CloudGlue is primarily designed for developers. Potential use cases include:

• Analyzing sales meetings
• Analyzing product demonstrations
• Building knowledge graphs from video content
• Enabling chatbots to answer questions based on video content
• Running aggregate analytics from video collections

Key Advantages:

• Effortless Setup: The tool simplifies the integration of video data into AI systems.
• Rapid Deployment: Set up in minutes, production-ready from day one.
• Focus on Development: CloudGlue enables developers to concentrate on product development, rather than handling complex data transformation processes.
• Scalable Insights: Supports scaling from quick transcripts to full multimodal insights.
• Off-the-Shelf Model Enhancement: Designed to improve the performance of existing off-the-shelf models.

Important Notes:

• Pricing information is not currently available. A free playground is offered for testing.
• Integration details beyond the API calls are not specified in the provided information.
• The documentation supports rapid development, enabling faster deployment and time-to-market.