Raspberry Pi 5 Multimodal RAG Local Assistant Kit – Query Your Private Knowledge Base Using Text & Images

Every part needed, pre-tested for compatibility, with an AI build companion trained on this exact project. Shipped from Bengaluru in 3-5 days.

What if your private documents, scanned notes, and photo collections formed a searchable AI brain that runs entirely on your desk—no cloud, no subscriptions, no data leaving your room? This kit guides you through building exactly that: a retrieval-augmented generation (RAG) system on Raspberry Pi 5 that accepts text and image queries and returns precise, context-aware answers from your own indexed files. Use it for research, exam prep, or a hardware-accelerated alternative to commercial note-taking apps—all while mastering edge AI deployment.

What You'll Build

You’ll install Ollama for local LLM inference, generate CLIP image embeddings from the Pi Camera Module 3, and store a vector database on the 512GB NVMe SSD. The system lets you type a question or snap a photo of a textbook page, whiteboard, or circuit diagram; it then retrieves the most relevant chunks from your personal documents and synthesises a concise answer. The result is a privacy-first multimodal assistant that sits on your local network, accessible via browser or custom API.

What You'll Learn

• Deploy a production-grade multimodal RAG pipeline on a single-board computer
• Optimise and quantise an LLM for smooth inference on Raspberry Pi 5’s 8GB RAM
• Generate and index CLIP embeddings for text-to-image and image-to-image retrieval
• Architect a low-latency retrieval stack using NVMe storage and I2S audio input

Kit Contents

Why Buy This Kit Instead of Sourcing Parts Separately

Who This Kit Is For

B.Tech ECE and CSE students working on final-year projects in edge AI, M.Tech researchers at IITs or NITs prototyping privacy-preserving assistants, and Smart India Hackathon teams needing offline computer vision pipelines will find this kit immediately useful. It’s also ideal for ATL Tinkering Lab mentors who want to demonstrate advanced retrieval concepts, and for self-taught developers exploring alternatives to cloud-dependent LLM apps.

Built and Backed by Compoden

Every Compoden kit ships with an AI build companion trained on this exact project — accessible via a QR code on the box, with WhatsApp and email backup. We’ve spent 10 years building projects for makers, schools, and institutions across India. If a part fails because of a manufacturing defect, replace it free within 7 days.