I'm a developer based in Addis Ababa. While the AI Boom is happening in the cloud, 35 million students in my region are being left behind because they have zero reliable internet and can't afford the data costs of hitting a GPT-5 API.

I built Ivy to solve this. It’s an educational co-pilot designed to run entirely on-device (Edge-Inference).

How it works:

Offline Inference: Optimized local LLMs running on $150 entry-level Android hardware.

Native Support: Integrated logic for local languages (Amharic) to bridge the cultural gap.

Sovereignty: The system is designed to function when the grid or the gateway is down.

I’ve documented the architecture and a 4-minute demo of the system running in a real-world environment here: https://builder.aws.com/content/39w2EpJsgvWLg1yI3DNXfdX24tt/aideas-ivy-the-worlds-first-offline-capable-proactive-ai-tutoring-agent

I’m currently in the quarter-finals of a global AWS challenge to get this the resources it needs to scale. I’m looking for technical feedback on the edge-inference logic and the sync protocols for when these devices do hit a 2G signal.

Happy to answer questions about the reality of building LLM-infrastructure in a zero-connectivity environment.