ConvoFlow
ConvoFlow transforms networking conversations into high-quality, personalized follow-up emails using AI.
Core trick
Uses GPT-5 to extract relationship signals from conversation notes, then drafts follow-up emails referencing specific discussion points.
Tags
Description
ConvoFlow transforms networking conversations into high-quality, personalized follow-up emails using AI. The problem: generic follow-ups have 15% response rates because they're forgettable and impersonal. ConvoFlow uses GPT-5 to analyze conversation context, extract relationship signals, and generate professional emails that reference specific discussion points and shared connections. This creates emails that feel like natural conversation continuations, boosting response rates to 60%+ while saving professionals hours of manual email crafting.
README excerpt
# ConvoFlow - AI Networking Assistant Transform networking conversations into relationship-building follow-up emails using AI-powered conversation analysis and personalized email generation. ## 🚀 Features - **Real-time Input Analysis**: Instant feedback on conversation quality with qualitative scoring - **GPT-5 Conversation Intelligence**: Deep analysis of relationship signals and communication style - **Personalized Email Generation**: AI-generated follow-up emails that reference specific conversation details - **Rule-based Input Optimization**: Fast, offline analysis for immediate feedback - **Professional UI**: Clean, intuitive interface with side-by-side input and analysis ## 🏗️ Architecture ``` convoflow/ ├── app.py # Main Streamlit application ├── requirements.txt # Python dependencies ├── lib/ │ ├── conversation_analyzer.py # GPT-5 conversation analysis │ ├── email_generator.py # AI email generation │ ├── input_analyzer.py # Rule-based input optimization │ └── openai_client.py # OpenAI API integration ├── utils/ │ ├── prompts.py # Validated GPT prompts │ └── validation.py # Input validation utilities └── tests/ # Unit and integration tests ``` ## 🚀 Data Flow <img width="1000" height="800" alt="image" src="https://github.com/user-attachments/assets/406f8a0d-1622-42fe-af6b-60a5e85ecbf3" /> ## 🛠️ Quick Start ### 1. Install Dependencies ```bash pip install -r req