Adding Voice and AI Assistants to Hardware Products: Connecting Devices to Large Language Models
Everyone wants their product to talk. How I connect small devices to cloud AI models reliably and affordably.
The problem clients bring: "We want our device to understand voice commands and answer questions, like an assistant. Our prototype works on a laptop but not on the device."
What is really going wrong
- AI SDKs assume a phone or server, not a microcontroller with limited memory.
- Waiting for a full response makes the device feel slow.
- No plan for what the device does when the network or AI service is unavailable.
- API keys embedded in firmware where anyone could extract them.
How I solve it
- Use a lightweight client built for embedded memory limits, with streaming responses.
- Let the model call functions on the device, so voice turns into real actions.
- Keep wake word and basic commands on the device, and use the cloud only when needed.
- Route requests through the client's own backend so keys never live on the device.
- Design graceful behaviour when offline.
What the client gets
A device that responds quickly, does useful things with what it hears, and keeps working sensibly when the internet does not.