Show HN: I built an app that tells you what to say in meetings (www.itsconvo.com)

Convo is a Show HN project that acts as a real-time AI meeting assistant: it listens to your calls, transcribes and analyzes the conversation on the fly, and suggests exactly what to say next. Beyond “autocompleting” your next line, it can answer questions about the meeting (“who volunteered to take action X?”), pull in relevant context from agendas or prior notes, and surface talking points or data snippets on demand. The pitch is instant, contextualized prompts that reduce friction in meetings—helping you join late, steer discussions, or avoid missing follow-ups. For the AI/ML community the app highlights practical, latency-sensitive uses of speech-to-text, speaker diarization, retrieval-augmented generation and conversational large models. Key technical challenges/implications include low-latency ASR and diarization, maintaining coherent context windows across a meeting, fast retrieval of related documents, and safe on-the-fly prompt engineering. It also raises privacy, consent, and security questions (call recordings, retention, corporate policy), plus risk of over-reliance or hallucinations from the model. Convo is a compact case study in integrating streaming ML pipelines with RAG and UX constraints—useful for teams building real-time assistants but a reminder to prioritize accuracy, transparency, and governance when deploying in the wild.