Is my video data uploaded to the cloud?

No. Edit Mind is built to be 100% local. All video processing, indexing, and AI analysis stay on your computer or local server.

What editing software does it support?

The commercial desktop app provides direct integration for DaVinci Resolve and Final Cut Pro, allowing you to move from search to timeline instantly.

Does it require a GPU?

While it can run on a CPU, a GPU is highly recommended for faster video indexing and analysis. It supports NVIDIA (via CUDA) and Apple Silicon (M1/M2/M3) chips.

How do I add my videos to the tool?

You can configure a host media path in your settings. The background service will then rescan those folders and index any existing or new video files.

Which AI models does it use for search and transcription?

It utilizes OpenAI Whisper for transcriptions, ChromaDB for vector storage, and can use Ollama or Google Gemini for natural language processing.

Can I use it on Linux?

Yes, the self-hosted version runs via Docker Compose and is compatible with any Linux environment that supports Docker.

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Video editing

Freemium

Edit Mind

Search your local video library like you'd describe to a friend. Uses AI for transcription, face recognition, and semantic search without the cloud.

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Rating

Reviews

Upvotes

3 months ago

Listed

Mac

GitHub

Video

Video Editing

Local AI

Semantic Search

Content Creation

Video Asset Management

Tool information

Provider

Ilias Had

Platforms

macOS

Windows

Linux

Docker

Languages

English

Added to directory

3 months ago

Last updated

about 1 month ago

Rating

Not available

Pricing

Freemium

About Edit Mind

What the tool does and who it's for

Edit Mind is a local-first video knowledge base that allows content creators and editors to search their footage using natural language. It functions as a local index of your video library, performing multi-modal analysis—including transcription, face recognition, and object detection—to enable semantic search. Unlike cloud-based solutions, Edit Mind runs 100% locally on your own hardware via Docker or a standalone desktop application, ensuring privacy and eliminating cloud subscription costs. It is designed for high-speed retrieval of specific scenes across hours of footage, with direct integration for professional tools like DaVinci Resolve and Final Cut Pro in its desktop version.

Key capabilities

Vector-Based Semantic Search: Use natural language to find specific scenes or objects across your entire video library.

100% Local Processing: All indexing, transcription, and analysis run on your machine to ensure total privacy.

Multi-Modal Analysis: Extracts metadata using AI for face recognition, transcription (Whisper), and object detection (YOLO).

NLE Integration: Direct integration with DaVinci Resolve and Final Cut Pro for seamless editing workflows (Desktop App).

Background Indexing: A dedicated service automatically monitors folders and processes new video files in the background.

Custom Face Metadata: Attach structured data to recognized faces to filter scenes by specific people or attributes.

Flexible AI Backends: Support for local LLMs via Ollama or integration with external models like Google Gemini.

GPU Acceleration: Utilizes local hardware (NVIDIA via CUDA or Apple Silicon) for high-performance processing.

Pricing

Freemium — plans below

Self-Hosted (Community)

Free

Runs via Docker
Full semantic search
Transcription and face recognition
Open source on GitHub
Community support

Desktop App (Early Bird)

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