
**The Problem** Hardware debugging is a two-handed task. You may be holding a multimeter, checking wiring, or soldering while also trying to search documentation, type into a chatbot, or scroll through a datasheet. Existing AI assistants are mostly text-based and often give generic advice without enough hardware context. **The Solution** CircuitMate is a voice-native AI agent built for embedded systems and hardware debugging. It supports platforms such as Arduino, ESP32, ESP8266, and Raspberry Pi Pico, along with sensors, motors, and common circuit issues. You can simply talk to it while working. When a problem is unclear, CircuitMate asks targeted questions about things like pin connections, component behavior, or error symptoms. It then narrows down the likely causes and suggests practical tests in a sensible order. If a question is unrelated to electronics, it redirects the conversation instead of going off-topic. The conversation is also transcribed into a scrollable log, so useful instructions can be referenced without interrupting the hardware work. **Technical Approach** CircuitMate uses AssemblyAI's Voice Agent infrastructure for real-time speech-to-text, language processing, and text-to-speech. The application is a lightweight single-page web app where microphone audio is streamed over WebSocket and responses are returned as speech. We also implemented an adaptive jitter buffer for audio playback. It monitors the timing between incoming audio chunks and dynamically adjusts playback buffering, helping maintain low latency on stable connections while reducing audio interruptions on unstable networks. **Why It Matters** CircuitMate explores how voice can make technical work more hands-free and natural. The same approach could extend beyond electronics to areas such as field service, mechanics, robotics, and research.
30 Sep 2026