Large Language Models or better Small Language Models (

Large Language Models or better Small Language Models ( #SLM) like #LUCIE are powerful but their true potential is unlocked when they’re connected to your own, secure knowledge base.

That’s where Retrieval Augmented Generation ( #RAG) comes in.

🔍 In this short video, we walk you through how LINAGORA’s open source RAG framework transforms your documents - emails, PDFs, videos, chat logs - into a smart, secure, and private assistant that actually knows your business.

✅ Why this matters:

• No need to train a custom model
• Real-time access to your internal knowledge
• Citations you can verify
• Total data security and partitioned access
• Fully LLM-agnostic (OpenAI or local models - you can choose)
• 100% Free & Open Source (no vendor lock-in)

💡 Built with modular architecture, scalable on Ray (https://www.ray.io/), on Milvus, created by Zilliz vector database and natively integrated with Twake Workplace, it’s the perfect foundation for digital sovereignty and AI-powered collaboration.

🎥 Check out the live demo in the video to see how RAG:

• Finds project details from meeting notes
• Extracts facts from graphs using OCR (with Docling 😉 Vincent Perrin)
• Synthesizes insights across domains
• Respects strict data boundaries

📅 [SAVE THE DATE] Join us for a live webinar on July 10 at 17:30 (Paris time) to dive deeper into the tech and get your questions answered!

Stay tuned for more info real soon!

Let’s build the future of AI openly, securely, and together.