Key Features

• •AI-Powered Video Analysis extracts metadata including face recognition, transcription, object detection, text detection, and scene analysis using multi-model embedding for comprehensive content understanding.
• •Vector-Based Semantic Search enables natural language queries through ChromaDB, allowing users to find video scenes by spoken words, objects, faces, or semantic concepts without exact keyword matching.
• •Local-First Operation runs fully on your own hardware using Docker, ensuring complete data privacy with no external cloud dependencies while supporting any computer or server.
• •Automated Video Indexing features a background service that watches for new video files, automatically queues them for processing, and maintains an up-to-date searchable library.
• •Multi-Format Support handles various video formats with transcoding capabilities, ensuring compatibility with different media types and seamless integration into existing workflows.
• •Self-Contained Deployment uses Docker Compose for easy setup, packaging all dependencies including PostgreSQL, ChromaDB, and ML services into portable containers.
• •Natural Language Interface allows intuitive search queries like 'a person smiling at sunset' or 'car driving in rain' with results ranked by semantic relevance to user intent.
• •Privacy-Respecting Design keeps all video processing and data storage on local infrastructure, giving users full control over their media without data sharing concerns.

Use Cases

• •Video Editors quickly locate specific shots or b-roll footage by searching for visual elements like 'sunset beach scene' or 'crowd cheering moment' without manual timeline scrubbing.
• •Content Creators find interview segments or talking points by searching transcribed dialogue, enabling efficient compilation of footage based on discussed topics or keywords.
• •Journalists and Researchers analyze video datasets for specific objects, faces, or events across multiple files, supporting investigative work and pattern recognition.
• •Families organize home videos by searching for people, locations, or events like 'birthday party 2023' or 'grandma telling stories' to create compilations and memories.
• •Educational Institutions manage lecture recordings by enabling students to search for specific topics discussed in class, improving study efficiency and content accessibility.
• •Security and Surveillance review footage by searching for specific objects, vehicles, or people across multiple camera feeds using natural language descriptions of events.

Who is this for?

Edit Mind targets video editors, content creators, journalists, researchers, and self-hosted enthusiasts who need to organize and search video libraries. It serves users with large video collections who value privacy and data control, preferring local processing over cloud services. The platform appeals to technical users comfortable with Docker deployment, as well as non-technical users through its commercial desktop app. It's ideal for professionals in media production, academic research, journalism, and personal archiving who require efficient video retrieval without compromising data security.