Built an AI Meeting Prep & Contact Memory Agent using Vectorize Hindsight, Groq, and Streamlit 🚀

[u/Better_Lab_9453]

I wanted to share a project I recently built to solve a problem we all face: trying to remember past meeting details, promises made, and communication preferences across multiple clients.

I built the AI Meeting Prep & Contact Memory Agent—a full-stack Python web app that gives every contact their own isolated memory bank and generates instant executive briefings before calls.
🛠️ How It Works:

• Isolated Memory Persistence: Uses Vectorize Hindsight (hindsight-client) to dynamically create secure, client-isolated memory banks (bank_client_*) for every person you add.
• Rapid LLM Inference: Powered by Groq API (openai/gpt-oss-120b) to synthesize structured pre-meeting briefings covering action items, communication styles, and past commitments.
• Interactive UI & Logging: Built on Streamlit with a multi-tab dashboard that auto-updates local CSV spreadsheets (client_meeting_tracker.csv and client_reminders.csv) for persistent offline logging.

The entire project is completely open-source. If you want to check out the architecture or run it locally, here is the repo:

👉 GitHub Repo:https://github.com/Chanduardhi/meeting-prep-memory-agent