Videos, images, and documents — all understood by local AI
Self-Hosted Multimodal RAG
Generative Media Manager : GeMM
Analyze videos, images, PDFs, Word, and Excel with VLM for cross-search using natural language. Visually present search results to avoid hallucinations. Fully self-hosted. No confidential data is sent externally.
Features
Key Features
Flexible Architecture
Deploy to your environment with Docker Compose. Process with local VLM while connecting to cloud LLM as needed. Full on-premises operation is also possible.
Multimodal Search Platform
Vectorize videos, images, and documents uniformly for natural language cross-search. Search results are presented visually to avoid hallucinations.
High-speed Vector Search
Fast ANN search with HNSW index using PostgreSQL + pgvector. Millisecond response even with millions of vectors. Integrates with existing SQL workflows.
Multiple Integration Options
Web UI, AI agent integration (ChatGPT / Claude / Copilot / Claude Code / Cursor), and REST API for internal system integration.
Use Cases
Various Applications
Internal Knowledge Search via Web UI
Cross-search meeting videos, manual videos, and training materials with natural language. Supports vague queries like 'the part about sales in last month's board meeting.' Directly search scenes in videos with timestamp results.
AI Agent Integration
Connect with AI agents using GeMM as a Retriever to build a multimodal knowledge base. Supports fully on-premises processing with local AI (Qwen3.5, etc.), and integrates with ChatGPT / Claude / Copilot / Claude Code / Cursor.
Internal System Integration via REST API
Analyze manufacturing line surveillance footage and inspection images. Improve quality control efficiency and traceability through anomaly detection and similarity search with past cases.
Try It Out
SaaS plan is now available.
Feel free to contact us for implementation consultation.