Deploying AI at the edge makes local public service tools practical and accessible. PreVillage connects citizens in Nepal to government services over WhatsApp. Powered by Gemma via llama.cpp on a Raspberry Pi, it cleans raw speech transcripts, reasons through user intent, and retrieves verified public sources directly on-device. Congrats... on the llama.cpp prize winner for the Gemma 4 Good Hackathon!show more

Read the technical write-up to explore their self-healing RAG pipeline and Raspberry Pi deployment:

Raspberry Pi + llama.cpp is the receipt that edge Gemma actually ships. Cleaning speech and routing intent on-device beats cloud-first for local public services.

Edge computing facilitates significant improvements in latency and privacy for public service delivery, especially in remote areas. Utilizing Gemma via llama.cpp on low-power hardware like a Raspberry Pi demonstrates a highly efficient way to deploy Large Language Models for localized intent reasoning and data cleaning. This architecture effectively bridges the digital divide by leveraging ubiquitous platforms like WhatsApp to deliver complex government services. How does the system manage the trade-off between model quantization and the accuracy required for processing diverse speech transcripts in Nepal?

You guys are always cooking something 💀🔥

Amazing! This is best use case of ai application even in remotest of areas but your enemy will be red tape and corruption. Praying for your success’

this is the kind of edge ai that actually matters. low infrastructure, local processing, and a real path to public services. raspberry pi doing useful work beats another flashy demo any day